MarketInsightsReports has published a report titled global Artificial Intelligence (AI) In Cyber Security Market research report 2021 that is a detailed observation of several aspects, including the rate of growth, technological advances, and different methodologies implemented by the primary current market players. The report is based on a collective analysis of data, which is obtained through primary and secondary research. It provides a systematic approach to the current and prospective scenario of this market.

The global Artificial Intelligence (AI) In Cyber Security Market will register a 27.3% CAGR in terms of revenue, and the market size will reach USD 23.10 billion by 2025.

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Top Companies in the global Artificial Intelligence (AI) In Cyber Security Market are
BAE Systems, Cisco, Fortinet, FireEye, Check Point, IBM, RSA Security, Symantec, Juniper Network, Palo Alto Networks, and Other.

By Type Outlook-
Machine Learning
Natural Language Processing
Other
Machine learning is taking the most market percentage, with over 69% market share.

By Application Outlook-
BFSI
Government
IT & Telecom
Healthcare
Aerospace and Defense
Other
BFSI, government and IT & telecom segments occupied the largest market share, while healthcare, aerospace and defense and other industries are expected to grow at a steady speed in future.

The report also takes into account the impact of the novel COVID-19 pandemic on the Artificial Intelligence (AI) In Cyber Security market and offers a clear assessment of the projected market fluctuations during the forecast period.

Browse full Artificial Intelligence (AI) In Cyber Security Market report description with TOC:
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Regional Analysis:

North America (The United States, Canada, and Mexico),

Asia-Pacific (China, India, Japan, South Korea, Australia, Indonesia, Malaysia, and Others),

Europe (Germany, France, UK, Italy, Russia, and Rest of Europe),

Central & South America (Brazil, and Rest of South America)

Middle East & Africa (GCC Countries, Turkey, Egypt, South Africa and Other)

Key Factors of the Artificial Intelligence (AI) In Cyber Security market report are
– A comprehensive evaluation of all opportunities and risks in the market.
– Artificial Intelligence (AI) In Cyber Security market current developments and significant occasions.
– A deep study of business techniques for the development of the market-driving players.
– Conclusive study about the improvement plot of the market for approaching years.
– Top to the bottom approach of market-express drivers, targets, and major littler scale markets.
– Favorable impressions inside imperative mechanical and publicize the latest examples striking the Artificial Intelligence (AI) In Cyber Security market.

Customization of the report
This report can be further customized according to the client’s specific requirements. No additional charges will be added for limited additional research.

The post Artificial Intelligence (AI) In Cyber Security Market Technological Trends and Business Opportunities 2021 To 2026 – Cisco, Fortinet, FireEye, Check Point, IBM appeared first on Artificial Intelligence.

The report also dispenses valuable statistics about market size, participant share, and consumption data in terms of key regions, along with an insightful gist of the behemoths in the Deep Learning market. The study of Deep Learning market highlights important aspects such drivers, challenges, restraints, and expansion prospects prevailing in this particular industry sphere.

Major Market Key Players:

• Advanced Micro Devices
• ARM Ltd
• Clarifai
• Entilic
• Google
• HyperVerge
• IBM
• Intel
• Microsoft
• NVIDIA

Deep Learning Market Segment by Types, covers:

• Software
• Hardware
• Service

Deep Learning Market Segment by End Use, can be divided into:

• Aerospace & Defense
• Automotive
• Manufacturing
• Healthcare
• Others

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A dedicated chapter on COVID-19 analysis has therefore been included in this versatile report to encourage future-ready business discretion aligning with post-COVID-19 market environment.

Deep Learning Market: Regional Segment Analysis

• North America
• Europe
• Asia Pacific
• Middle East & Africa
• Latin America

Some of the key questions answered in the report include:

1. What is the overall structure of the market?
2. What was the historical value and what is the forecasted value of the market?
3. What are the key product level trends in the market?
4. What are the market level trends in the market?
5. Which of the market players are leading and what are their key differential strategies to retain their stronghold?
6. Which are the most lucrative regions in the market space?

Table of Contents:

1. Global Deep Learning Market Overview
2. Deep Learning Economic Impact on Industry
3. Deep Learning Market Competition by Manufacturers
4. Production, Revenue (Value) by Region
5. Supply (Production), Consumption, Export, Import by Regions
6. Production, Revenue (Value), Price Trend by Type
7. Deep Learning Market Analysis by Application
8. Deep Learning Manufacturing Cost Analysis
9. Industrial Chain, Sourcing Strategy and Downstream Buyers
10. Marketing Strategy Analysis, Distributors/Traders
11. Deep Learning Market Effect Factors Analysis
12. Global Deep Learning Market Forecast

Conclusively, the report describes the performance of the key product and application segments in the Deep Learning Market in each regional market. Likewise, the competitive dynamics of each regional market have been elaborated by providing information on the hierarchy among the major players operating within it. This provides a thorough and detailed analysis of the global market. The report also provides forecasts for 2021-2028 for each product, application and geographical segment of the global market.

About Us:

Research N Reports is a new age market research firm where we focus on providing information that can be effectively applied. Today being a consumer-driven market, companies require information to deal with the complex and dynamic world of choices, where relying on a soundboard firm for your decisions becomes crucial. Research N Reports specializes in industry analysis, market forecasts and as a result getting quality reports covering all verticals, whether be it gaining perspective on current market conditions or being ahead in the cutthroat global competition. Since we excel at business research to help businesses grow, we also offer to consult as an extended arm to our services which only helps us gain more insight into current trends and problems. Consequently, we keep evolving as an all-rounder provider of viable information under one roof.

The post Deep Learning Market Size, Growth Analysis, Opportunities and Forecast To 2028 | Advanced Micro Devices, ARM Ltd, Clarifai appeared first on Artificial Intelligence.

This intelligence report includes research based on current scenarios, historical records and future forecasts. In this research report, specific data on various aspects such as type, size, application and end user were checked. It offers a 360-degree overview of the competitive landscape of industries. The SWOT analysis was used to understand the strengths, weaknesses, opportunities and threats faced by companies. This helps companies understand the threats and challenges ahead. The Intelligent Apps market is growing steadily and the CAGR is expected to improve over the forecast period.

The intelligent apps use the functionalities of AI, cognitive computing, big data and analytics, and others to provide an advanced analytical output that can be utilized for different applications, such as prioritizing emails, security tooling, virtual personal assistants, virtual customer assistants, enterprise applications, and others.

Our report covers the critical market information considering the rapid progression & wide-ranging impacts of COVID-19 virus on the global economy, and help you understand which countries or business segments are likely to get most affected.

Few of the main competitors currently working are –

IBM, Apple Inc., Ayasdi AI LLC, BigML, Inc., Google, H2O.ai, Hewlett Packard Enterprise Development LP, Microsoft, Oracle, SAP SE

THE INSIGHT PARTNERS RESEARCH REPORT GUIDANCE

The report provides qualitative and quantitative trends of global Intelligent Apps across type, deployment, organization size, end-user, and geography.
The report starts with the key takeaways (chapter two), highlighting the key trends and outlook of the global Intelligent Apps .
Chapter three provides the research methodology of the study.
Chapter four further provides ecosystem analysis along with PEST analysis for each region.
Chapter five highlights the key industry dynamics in the Intelligent Apps , including factors that are driving the market, prevailing deterrent, potential opportunities as well as future trends. Impact analysis of these drivers and restraints is also covered in this section.
Chapter six discusses the global Intelligent Apps scenario, in terms of historical market revenues, and forecast till the year 2027.
Chapter seven to eleven discuss Intelligent Apps segments by type, deployment, organization size, end-user, and geography across North America, Europe, Asia-Pacific, Middle East and Africa, South and Central America. They cover market revenue forecast, and factors driving and governing growth.
Chapter twelve describes the industry landscape analysis. It provides detailed description of various business activities such as market initiatives, new developments, mergers and joint ventures globally along with a competitive landscape.
Chapter thirteen provides the detailed profiles of the key companies operating in the global Intelligent Apps . The companies have been profiled on the basis of their key facts, business description, products and services, financial overview, SWOT analysis, and key developments.
Chapter fourteen, i.e. the appendix is inclusive of a brief overview of the company, glossary of terms, contact information, and the disclaimer section.

The post INTELLIGENT APPS MARKET YEAR 2020 BUSINESS OPPORTUNITIES TO 2027 BY KEY PLAYERS. appeared first on Artificial Intelligence.

Analysis of COVID-19 Impact on the Data Science and Machine Learning Platforms Market with Key Players Analysis

The report highlights the current impact of COVID-19 on the Data Science and Machine Learning Platforms market along with the latest economic scenario and changing dynamics of the market. The report on the Data Science and Machine Learning Platforms market is an all-inclusive document comprising crucial information about top players, market trends, pricing analysis, and overview of the market for the forecast period. It consists of valuable information and an in-depth analysis of primary and secondary drivers, market share, leading segments, and regional analysis. The report also encompasses details on the key competitors and their strategies, such as mergers, acquisitions, recent technological developments, and the business landscape.

Competitive Analysis:

The competitive analysis covers key players and the innovations and business strategies undertaken by them. The report captures the best long term growth opportunities for the sector and includes the latest process and product developments. The report includes basic information of the companies along with their market position, historical background, and market capitalization and revenue. The report covers revenue figures, market growth rate, and gross profit margin of each player based on regional classification and overall market position. The report provides a separate analysis of the recent business strategies such as mergers, acquisitions, product launches, joint ventures, partnerships, and collaborations.

Key features of the Report:

The report covers extensive analysis of the key market players in the market, along with their business overview, expansion plans, and strategies. The key players studied in the report include:
AWS, Databricks, Dataiku, DataRobot, Domino, Google, H2O.ai, IBM Watson Studio/Watson ML, KNIME, Microsoft Azure, RapidMiner, SageMaker, SAP

Market Breakdown:

The market breakdown provides market segmentation data based on the availability of the data and information. The market is segmented on the basis of types and applications.

Data Science and Machine Learning Platforms

To understand the global Data Science and Machine Learning Platforms market dynamics, the market is analyzed across major global regions and countries. Market Expertz provides customized specific regional and country-wise analysis of the key geographical regions as follows:

North America: USA, Canada, Mexico
Latin America: Argentina, Chile, Brazil, Peru, and Rest of Latin America
Europe:K., Germany, Spain, Italy, and Rest of EU
Asia-Pacific: India, China, Japan, South Korea, Australia, and Rest of APAC
Middle East & Africa: Saudi Arabia, South Africa, U.A.E., and Rest of MEA
The report considers:

Historical Years: 2017-2018
Base Year: 2019
Estimated Year: 2020
Forecast Years: 2020-2027
Benefits of Data Science and Machine Learning Platforms Market Report:

In-depth understanding of the market size of Data Science and Machine Learning Platforms market
Easy identification of growth opportunities and key product development strategies
Comprehensive historical and accurate forecast data for the Data Science and Machine Learning Platforms market to ease the decision-making process
Production and consumption ratio, import/export data, and companies’ market positions explained in detail with graphs and charts to aid in formulating lucrative strategies.
Strategic recommendations about partners and suppliers
Report Overview with TOC:

Research report overview along with COVID-19 impact analysis
Regional analysis of growth trends
Competitive landscape along with estimated revenue share, market share, and market concentration ratio
Segmentation data based on product types
Segmentation data based on applications

Thank you for reading our report. Customization of the report is also available on the basis of region and countries. Kindly get in touch with us for more information regarding the report and its customization. Our team will ensure the report is best suited according to your needs.

The post DATA SCIENCE AND MACHINE LEARNING PLATFORMS MARKET INSIGHTS BUSINESS OPPORTUNITIES 2027 appeared first on Artificial Intelligence.

This elaborate global research output outlining the various facets of the Microservices market reveals valuable insights that could trigger exponential growth in the Microservices market, with sumptuous references about competition spectrum, growth friendly marketing strategies, tactical business discretion as well as dynamic segmentation, which together influence a highly decisive growth trail in the global Microservices market.

The various components and growth propellants such as dominant trends, existing challenges and restrictions as well as opportunities have also been discussed at length. The report is designed to guide the business decisions of various companies and research experts who look forward to market profitable decisions in the Microservices market.

The study encompasses profiles of major companies operating in the Microservices Market. Key players profiled in the report includes:

IBM
Microsoft
Salesforce
Infosys
NGINX
Oracle
Pivotal Software
Syntel
SmartBear Software
Marlabs
RapidValue Solutions
Kontena
Macaw Software
Unifyed
RoboMQ
Idexcel

Global Microservices market research report presentation demonstrates and presents an easily understandable market depiction, lending crucial insights on market size, market share as well as latest market developments and notable trends that collectively harness growth in the global Microservices market. This detailed and meticulously composed market research report on the Microservices market discussed the various market growth tactics and techniques that are leveraged by industry players to make maximum profits in the Microservices market even amidst pandemic situation such as COVID-19.

Scope of the Report
The discussed Microservices market has been valued at xx million US dollars in 2019 and is further projected to grow at xx million US dollars through the forecast span till 2024, growing at a CAGR of xx% through the forecast period.

By the product type, the market is primarily split into

On-Premise
Cloud Based
By the end-users/application, this report covers the following segments

Retail and Ecommerce
Healthcare
Media and Entertainment
Banking
Financial Services
and Insurance
IT and ITes
Government
Transportation and Logistics
Manufacturing
Telecommunication
Others

For the convenience of complete analytical review of the Microservices market, 2019 has been identified as the base year and 2020-24 comprises the forecast period to make accurate estimation about the future growth prospects in the Microservices market.

Regional Analysis of the Microservices Market:
Additionally, the report serves as a convenient guide to design and implement potential growth steering activities across select regional pockets in the Microservices market. Frontline players and their effective growth strategies are also enlisted in the report to emulate growth.

– North America (U.S., Canada, Mexico)
– Europe (U.K., France, Germany, Spain, Italy, Central & Eastern Europe, CIS)
– Asia Pacific (China, Japan, South Korea, ASEAN, India, Rest of Asia Pacific)
– Latin America (Brazil, Rest of L.A.)
– Middle East and Africa (Turkey, GCC, Rest of Middle East)

Seven Pointer Guide for Report Investment
• A complete documentation of historical, current events as well as future predictions concerning market value and volume
• Leading industry best practices and growth friendly initiatives by dominant players
• A thorough, in-depth analytical review of the Microservices market
• A complete synopsis of major market events and developments
• A methodical reference of the dominant alterations in market dynamics
• A detailed take on market events, developments as well as tactical business decisions
• An illustrative reference point determining market segmentation

Further in the subsequent sections of the report, readers can get an overview and complete picture of all major company players, covering also upstream and downstream market developments such as raw material supply and equipment profiles as well as downstream demand prospects

With unfailing market gauging skills, has been excelling in curating tailored business intelligence data across industry verticals. Constantly thriving to expand our skill development, our strength lies in dedicated intellectuals with dynamic problem solving intent, ever willing to mold boundaries to scale heights in market interpretation.

The post Global Microservices Market Growth Rate and Opportunities By 2025 – With COVID-19 Outbreak appeared first on Artificial Intelligence.

The bright future of the planet appears to be in grip of Artificial Intelligence (AI) technology. From industry giants like Amazon and Google to even small startups in India are driving digital evolution with adoption of AI into their businesses. Along with the companies, even their leaders have adapted to the vision focusing on AI-centric growth that can operate on algorithms and hence enable better customer experience.

The appeal of the technology is so at the peak that AI career profiles are becoming more and more famous in the market. Emerging trends of AI along with its subset machine learning has made it the most remarkable career in tech-industry.

Here we have enlisted top 10 job profiles, along with their hottest vacancy, seeking artificial intelligence and machine learning skills.

1. Amazon (New Delhi)- Business Development Manager

Role Description:

Professionals with broad and deep experience in both the business and technical aspects of cloud computing, especially in artificial intelligence (AI) and machine learning (ML) are suitable for the post of AI Business Development Manager. Having rich experience understanding and influencing compute technology choices and building programs to remove obstacles to adoption with public sector customers (governments, educational institutions, non-profits) can add up to the resume well. The Business Development Manager in general, helps business leaders and technologists adopt new cloud services and envision a future where smarter machines solve complex business problems.

Responsibilities:

•  Build a strong understanding of AI/ML technology and related industry developments, including certain companies’ services.

•  Communicate internally and externally about company’s AI/ML approach, value proposition, and offerings. Help field teams understand AI/ML services and help customers successfully adopt them.

•  Understand and uncover customers’ challenges in adopting AI/ML, and show how company solutions can help them provide new services, new capabilities, and new efficiencies.

•  Work with partners, internal teams, and customers to determine best use-cases, deployment, and adoption of AI/ML and related technologies, etc.

•  Work closely with global account teams of the company and sales and technical leadership to build programs that accelerate adoption of AI/ML, including generating technical content and white papers.

•  Define and deploy AI/ML campaigns and work with sales and field teams to implement them.

•  Identify and remove obstacles that block adoption of AI/ML and related workloads.

Qualification & Eligibility:

•  10 years or more of relevant technical leadership, product management, business development, in and around information technologies.

•  3 years or more of experience in AI/ML (e.g., product management, business development, technical marketing, etc.).

•  1 or more years of experience with public cloud computing services.

•  Bachelor’s degree in computer science, engineering or related technical degree.

•  In-depth experience in AI/ML technology, market dynamics, and customer requirements.

•  Demonstrated ability to think strategically about business, product, and technical challenges.

•  Demonstrated ability to build and scale programs that remove blockers to customer adoption and accelerate adoption.

•  Strong organizational, presentation, and writing skills.

Technical and Other Knowledge:

The ideal candidate for the job will possess technical expertise in AI and ML, along with a diverse technical, IT management, and/or engineering background. The person need to have knowledge of cloud computing, industry trends, and product developments as well.

The role of business development manager requires a strong passion for working with customers and partners, a high level of comfort navigating ambiguity, and attention to detail. Candidate will need to travel for face-to-face customer engagements, internal conferences, and industry events.

Salary Range:

Average Salary Ranges From 5 to 7 lac per annum.

2. Accenture (Bengaluru)-AI Team Leader

Role Description:

The person will be a critical member of an engineering team working on architecture, developing and augmenting cutting edge AI technology, which is a crucial part of our next generation AI based financial service platform and leading a team of R&D Engineers.

He/she should be master of almost everything including Artificial Intelligence, Machine Learning/Natural Language Processing (practical or/& computational linguistics)/ Deep Learning (text/vision/speech)/Reinforcement Learning (practical applications).

Responsibilities:

The selected candidate will be responsible for the entire development cycle of the solution, turning an idea into a working product, including, definition, implementation, testing and debugging. Optionally also, discussion with partners and strategic customers. He/she should be able to lead a team while adapting to AI technologies with consumer-centric approach.

Qualification & Eligibility:

•  At least 3-years hands-on experience with machine learning and neural networks and overall 5-8 years of experience in AI centric profile.

•  Good theoretical understanding of CNN RNN, supervised learning, reinforcement learning.

•  Ability to take a task from concept to full implementation.

•  Creative thinking.

•  Experience in data collection in simulation and field.

•  Experience in DNN framework infrastructure (TensorFlow Caffe etc).

•  Ability to lead team and interact with other teams.

•  MATLAB/python as mother language.

 Technical and Other Knowledge:

•  Familiar with Java / J2EE, Python.

•  Familiar with Apache OpenNLP or NLTK, ClearTK etc.

•  Expertise with NLP algorithms like Entity Recognition and Extraction, Text Classification, Query Parsers.

•  Understands Linguistics and the underlying algorithms behind NLP.

•  Familiar with NLP in an Internationalised Context.

•  Familiarity with AWS, Linux, Unix.

•  Familiarity with Git, SVN, Jira.

•  Familiarity with Agile Tools and Methodologies.

Salary Range:

Average Salary Ranges From 6 to 8 lac per annum.

3. Amazon (Bengaluru)-Data Scientist

Role Description:

As a Data Scientist, the candidate will be responsible for modeling complex problems, discovering insights and identifying opportunities through the use of statistical, machine learning, algorithmic, data mining and visualization techniques. The person will need to collaborate effectively with internal stakeholders and cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards.

The candidate should be able to apply a breadth of tools, data sources and analytical techniques to answer a wide range of high-impact business questions and present the insights in concise and effective manner. Additionally, the candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business.

Responsibilities:

•  Use predictive analytics and machine learning techniques to solve complex problems and drive business decisions.

•  Employ the appropriate algorithms to discover patterns of risks, abuse and help reduce bad debt.

•  Design experiments, test hypotheses, and build actionable models to optimize company operations.

•  Solve analytical problems, and effectively communicate methodologies and results.

•  Build predict models to forecast risks for product launches and operations and help predict workflow and capacity requirements for company operations.

•  Draw inferences and conclusions, and create dashboards and visualizations of processed data, identify trends, anomalies.

•  Work closely with internal stakeholders such as business teams, engineering teams, and partner teams and align them with respect to your focus area.

 Qualification & Eligibility:

•  Bachelor’s Degree in any quantitative discipline such as Statistics, Mathematics, Quantitative Finance or Operational Research.

•  At least 3 years of experience working in Analytics / Business Intelligence environment.

•  Experience in working with databases and SQL in a business environment.

•  Prior experience in design and execution of analytical projects.

•  Worked extensively in large scale databases and data warehouses.

•  Experience in e-commerce / on-line companies in fraud / risk control functions.

•  Experience in statistical techniques such as classification, clustering, regression, statistical inference, collaborative filtering, and natural language processing, experimental design, social networking analysis, feature engineering, etc.

•  Compelling communication and influencing skills and participation in winning the support of management and influence the course of major strategic decisions.

 Technical and Other Knowledge:

•  Demonstrated use of analytical packages and query languages such as SAS, SPSS and SQL.

•  Experience/knowledge of advanced machine learning techniques such as GBM, random forest, etc.

•  Coding skills in one of the modern languages Java, Python, Scala, R.

•  Experience with visualization technologies such as Tableau.

 Salary Range:

Average Salary Ranges From 7 to 10 lac per annum.

4. Wipro (Bengaluru)-ML Architect

Role Description:

The candidate will be entitled to build scalable machine learning systems and data-driven products working with cross functional teams Working w/ cloud services like AWS, Microsoft, IBM, and Google Cloud Working w/ one or more of the following Natural Language Processing, text understanding, classification, pattern recognition, recommendation systems, targeting systems, ranking systems or similar.

Responsibilities:

•   Research, design, develop, and modify computer vision and machine learning algorithms and models.

•   leveraging experience with technologies such as Caffe, Torch, or TensorFlow.

•   Shape product strategy for highly contextualized applied ML/AI solutions by engaging with customers, solution teams, discovery workshops and prototyping initiatives.

•   Help build a high-impact ML/AI team by supporting recruitment, training and development of team members.

•   Serve as evangelist by engaging in the broader ML/AI community through research, speaking/teaching, formal collaborations and/or other channels.

•   Designing integrations of and tuning machine learning & computer vision algorithms.

•   Research and prototype techniques and algorithms for object detection and recognition Convolutional neural networks (CNN) for performing image classification and object detection.

Qualification & Eligibility:

Have experience 2-5 years of work or educational experience in Machine Learning or Artificial Intelligence Creation and application of Machine Learning algorithms to a variety of real-world problems with large datasets.

Have Contribution to research communities and/or efforts, including publishing papers at conferences such as NIPS, ICML, ACL, CVPR, etc.

Technical and Other Knowledge:

•   Familiarity with Embedded Vision Processing Systems Open source tools & platforms Statistical Modelling, Data Extraction, Analysis, Construct, train, evaluate and tune neural networks

•   Java

•   C++

•   Python

•   Deep Learning frameworks such as Caffe OR Torch OR TensorFlow

•   Image/video vision library like OpenCV, Clarafai, Google Cloud Vision etc

•   Supervised & Unsupervised Learning

•   Developed feature learning, text mining, and prediction models (eg, deep learning, collaborative filtering, SVM, and random forest) on big data computation platform (Hadoop, Spark, HIVE, and Tableau)

•   Tableau, Hadoop, Spark, HBase, Kafka

Salary Range:

Average Salary Ranges From 4 to 6 lac per annum.

5. Google (Hyderabad)-Machine Learning Engineer

Role Description:

The person will help the company create artificial intelligence products. He/she will be entitled to create machine learning models and retraining systems. To do this job successfully, the person needs exceptional skills in statistics and programming. Having knowledge of data science and software engineering can probably get him the desired job.

•   The ultimate goal of ML Engineer will be to shape and build efficient self-learning applications.

Responsibilities:

•   Designing and developing machine learning and deep learning systems.

•   Running machine learning tests and experiments.

•   Implementing appropriate ML algorithms.

•   Study and transform data science prototypes.

•   Design machine learning systems.

•   Research and implement appropriate ML algorithms and tools.

•   Develop machine learning applications according to requirements.

•   Select appropriate datasets and data representation methods.

•   Run machine learning tests and experiments.

•    Perform statistical analysis and fine-tuning using test results.

•   Train and retrain systems when necessary.

•   Extend existing ML libraries and frameworks.

•   Keep abreast of developments in the field.

Qualification & Eligibility:

•   Qualification and relevant work experience in same field is required.

•   Proven experience as a Machine Learning Engineer or similar role.

•   Ability to work in a team.

•   Outstanding analytical and problem-solving skills.

•   BSc in Computer Science, Mathematics or similar field.

•   Master’s degree is a plus.

Technical and Other Knowledge:

•   Understanding of data structures, data modeling and software architecture.

•   Deep knowledge of math, probability, statistics and algorithms.

•   Ability to write robust code in Python, Java and R.

•   Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn).

•   Excellent communication skills.

Salary Range:

Average Salary Ranges From 4 to 7 lac per annum.

6. Microsoft (Hyderabad)-AI Engineer

Role Description:

The person will be responsible for commercialization of Artificial Intelligence, Cognitive Computing and Machine Intelligence Technologies for company’s businesses. Currently, companies are looking for well knowledge and experienced engineer who is keen to involve in new initiative of AI-nization projects across companies.

AI Engineer is expected to be familiar with wider scope of knowledge and experiences on designing and implementing of AI applications by applying available cognitive computing APIs and machine learning technologies from both internal and external companies.

Responsibilities:

•   AI Engineer is responsible forunderstanding the business problems.

•   Identifying/applying right AI or cognitive computing technologies to solve problems and involving in formulation and execution of technologies recipes for commercial deployment.

•   Understand the business problem, challenge of existing technologies and areas of application for AI technologies.

•   Identify and choose right AI or cognitive computing technologies for solving problems and formulate AI recipes for development.

•   Develop required machine learning models or prototype applications applying formulated AI recipes and verify the problem/solution fit

•   Involve in development of AI Platform and AI-nization projects.

 Qualification & Eligibility:

•   Minimum 3 years of development experience using one of JAVA, C, C++ or python languages.

•   Minimum 3 years of experience in web application development.

•   Minimum 2 years of experience in building of API driven interface development.

•   Experience in developing cloud applications running on Microsoft Azure, Amazon Web Service, Google Cloud, IBM Bluemix etc.

•   Experience in designing and implementing systems using emerging technology.

•   Experience in agile software development or similar methodologies.

•   Software prototyping.

•   Ability to learn new and emerging technologies.

•   Excellent verbal and written communication skills.

•   Demonstrated ability to deliver working solutions on a tight schedule.

•   Strong analytical thinking and problem-solving skills.

 Technical and Other Knowledge:

•   Artificial Intelligence, Cognitive Computing, APIs, Machine Learning, Deep Learning Technologies.

•   Semantic Web, Knowledge Engineering, Natural Language Processing.

•   Experiences with RDBM databases, NoSQL Database, Graph Database.

•   Experience in search platform such as Solr, Elastic Search.

•   Voice Recognition/Synthesis.

Salary Range:

Average Salary Ranges From 7 to 13 lac per annum

7. Amazon (Delhi)-ML Specialist

Role Description:

Machine Learning Specialist is a professional specialized in developing Machine learning, which can “learn” from or adapt to the data and make predictions.

The candidate should be bright & passionate about Machine Learning. He/she should be a team player who strives for engineering and technical excellence and enjoys in bringing innovation in a fast-paced environment.

The ML Specialist position offers excellent development prospects, the ability to develop skills to the highest level and be compensated with a competitive salary and fantastic benefits package.

Responsibilities:

•   Design and develop machine learning algorithms.

•   Discover, design, and develop analytical methods to support novel approaches of data and information processing.

•   Design and develop novel algorithms.

•   Perform explanatory data analyses.

•   Generate and test working hypotheses.

•   Prepare and analyze historical data and identify patterns.

•   Provide technical support for program management and business development activities including proposal writing and customer development.

•   Own and manage knowledge sharing within a community.

Qualification & Eligibility:

•   Education and Experience PhD in computer science, engineering, or related field with focus on Machine Learning.

•   MSc with machine learning focus plus 5+ years professional work experience.

Technical and Other Knowledge:

•   Experience with Bayesian optimization, Distributed learning algorithms, Predictive modeling.

•   Core Skills Excellent C++ development skills on Linux platforms (C++, Java, Python).

•   Experience developing software as part of a team.

Salary Range:

Average Salary Ranges From 12 to 15 lac per annum.

8. Bosch Group (Bengaluru)-ML Intelligent System Researcher

Role Description:

The companies with vacancy for ML Intelligent System Researcher are looking for creative & motivated researchers to work on topics related to Pervasive Computing/Intelligent Systems. The candidate is expected to have the ability to explore real life problems and identify the research challenges as part of the team engaged in bringing Intelligence to the next generation of Intelligent Systems using Machine Learning. The candidate will work as part of a talented team, supported by a software engineering team. He/she will be among the first to see and use this technology to solve real problems in ways never attempted by others.

The ideal candidate should have the ability to perform foundation research, to take initiative, to work in international teams and the necessary development/implementation skills to accomplish the proof of concept.

Responsibilities:

•   Research and develop innovative ML strategies for challenging problems that will affect future products.

•   Collaborate with broader teams across company to transfer AI/ML solutions.

•   Grab opportunities to provide technical mentorship and guidance, prepare technical reports for publication and conference talks.

•   Be self-motivated, excellent problem solver, and a fast learner.

•   Quick to forge relationships and comfortable with change and ambiguity.

•   Strong programming skills with tried experience crafting, prototyping, and delivering advanced algorithmic solutions.

Qualification & Eligibility:

•   PhD. from reputed Indian institutes (IISc, IITs, IIITs, etc.) or from reputed international institutes with good track record of publications in the areas of Computer Science/ Electronics and Communications Engineering/ Electrical and related branches with background in Machine Learning and application of Machine Learning to develop Intelligent Systems.

•   PhD. could be any of the areas of:

• Good knowledge on any of the below topics:

• • • Machine Learning for Intelligent Systems
    • Pervasive Computing
    • Context Aware Systems
    • IoT Data Analytics
  • Familiarity with programming languages: Python/R/Java/
    • Statistical Learning Theory
    • Time Series Analysis
    • Probabilistic Graphical Models
    • Reinforcement Learning
  • Ability to design experiment and create proof-of-concept deployments
  • Excellent verbal and written communication skills
  • Excellent presentation and mass communication skills
  • Entrepreneurial skills/experience

 Salary Range:

Average Salary Can Vary From 4 to 24 lac per annum (Depending On Location And Work Experience).

9. Adobe (Delhi NCR – Greater Noida)-ML Applied Research Scientist

Role Description:

The companies are looking for an expert in machine learning to help them extract value from their data. The ideal candidate will lead all the processes from data collection, cleaning, and pre-processing, to training models and deploying them to production.

The person will be passionate about machine learning and stay up-to-date with the latest developments in the field.

Responsibilities:

•   Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress.

•   Managing available resources such as hardware, data, and personnel so that deadlines are met.

•   Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability.

•   Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world.

•   Verifying data quality, and/or ensuring it via data cleaning.

•   Supervising the data acquisition process if more data is needed.

•   Finding available datasets online that could be used for training.

•   Defining validation strategies.

•   Defining the pre-processing or feature engineering to be done on a given dataset.

•   Defining data augmentation pipelines.

•   Training models and tuning their hyper-parameters.

•   Analyzing the errors of the model and designing strategies to overcome them.

•   Deploying models to production.

Qualification & Eligibility:

•   PhD degree in Machine Learning / Data Science / Statistics or Masters with 4+ years of experience in the aforementioned fields.

•   Deep knowledge of fundamentals of AI, Machine / Deep Learning, Data Mining and Predictive Modelling is required with solid experience in applying these techniques on real world problems.

•   Interdisciplinary skills in Big Data Technologies, ETL, statistics and causal inference is desirable.

•   Hands on experience in solution building, deployment, testing, and release processes using version control and continuous integration is desirable.

Technical and Other Knowledge:

•   Strong skills in software engineering practices (Design, Development and Requirement Management) with expertise in applicable programming languages and frameworks such as scikit-learn, XGBoost, Pytorch, Spacy, H2O.

•   Strong analytical, written and verbal communication skills.

•   Demonstrated ability to propose novel solutions to problems, performing experiments to prove feasibility of solutions and working to refine the solutions into real world context.

•   Proficiency with a deep learning framework such as TensorFlow or Keras.

•   Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas.

•   Expertise in visualizing and manipulating big datasets.

•   Proficiency with OpenCV.

•   Familiarity with Linux.

•   Ability to select hardware to run an ML model with the required latency.

Salary Range:

Average Salary Can Vary From 12 to 14 lac per annum.

 10. JP Morgan Chase & Co. (Hyderabad)-Data Scientist – Vice President

Role Description:

As Vice President and Data Scientist of the company, the candidate will be responsible for creating the overall AI roadmap for the company and build a cohesive and comprehensive AI strategy for execution of the plan as well as provide technical guidance and align company objectives with development plans. The person will champion AI advancement and lead major strategic and cross-functional initiatives to drive implementation of the roadmap. He/she will oversee AI related research and development and work with multiple teams to develop and implement innovative algorithms and architectures.

Responsibilities:

•   Work with the other executive of the team to create an AI roadmap and strategy that aligns with company business goals.

•   Provide technical leadership and expertise for research and development of AI technology for our autonomous driving solution.

•   Help guide the team design, develop, implement, and evaluate both traditional as well as deep learning solutions.

•   Manage and lead a cross functional team of diverse and creative individuals and build a culture of innovation and execution.

•   Work on building efficient workflow for experimenting, developing, and testing AI algorithms and architecture including data collection and annotation.

•   Focus on developing technology that is high performing and suitable for implementation in a real-world production environment and meets the product and business requirements.

•   Keep abreast of latest development of AI and ML ideas and algorithms both from academic and industry.

 Qualification & Eligibility:

•   PHD in computer science or related fields with AI/ML specialization.

•  Proven track record of 12+ years of progressive data science and ML/AI experience, with 3+ years in a significant leadership position managing large tech teams that designed, developed, and launched complex AI solutions.

•   Previous experience autonomous driving projects, especially in perception, predictions and motion planning, is preferred.

•   Demonstrated track record of successfully hiring, motivating, and retaining talented engineers.

•   Knowledge of machine learning, information retrieval, analytics, statistics, deep learning techniques.

 Technical and Other Knowledge:

•   Hands on experience in deep learning platform (such as Tensorflow) and models (such as DNN, CNN, RNN, GAN).

•   Experience and experience with GPU and CPU based efficient and scalable compute platform for deep learning.

•   Experience delivering cloud-based solutions at scale.

•   Understanding of security and compliance constraints is a plus.

•   Experience in development of multi-threaded event driven serving systems in C++/Python.

•   Competent in fundamental data structures, algorithms, and computer system.

•   Strong verbal and written communication skills.

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