Accenture’s Artificial Intelligence team focuses on getting machines to do things that we would call intelligent behavior. Intelligence – whether artificial or otherwise – does not have a precise definition, but there are many activities and behaviors that are considered intelligent when exhibited by humans and animals. Examples include seeing, learning, using tools, understanding human speech, reasoning, making good guesses, playing games, and formulating plans and objectives. AI team in Accenture Operations focuses on how to get machines or computers to perform these same kinds of activities, though not necessarily in the same way that humans might do them.

General Summary:

We are looking for an exceptional hands-on research scientist with a proven track record of experience in applying machine learning methods towards solving real-world problems through Knowledge Representation & Reasoning (KRR), Speech Recognition, Unsupervised Learning, Reinforcement Learning to name a few. You will be joining a world-class, multidisciplinary team and will be participating in cutting-edge research in machine intelligence and artificial intelligence. You will be providing quality answers to large-scale problems with broad impact.

Duties & Responsibilities:

Responsible for artificial intelligence/machine learning technology and application analysis, understand latest industrial and academic developments in AI/ML,
Develop new ideas and apply AI/ML to specific product challenges across Accenture Operations team.
Study and innovate in artificial intelligence/machine learning and its application in diverse domains.
Design competitive AI/ML services and user experience for next generation devices and create prototypes for demonstration.
Collect, synthesize, and propose requirements and create effective product/feature roadmap.
Work with the rest of the team to integrate these algorithms into larger solutions
Work with development teams to mature these algorithms into production quality programs




Skills & Abilities – (Technical & General):

Minimum 7-10 yrs. relevant experience post MS or 5-7 yrs. relevant experience post Ph D course. And hands on experience in Development of end to end product development based on Machine learning or Deep learning is mandatory. Exceptional hands-on research scientist with a proven track record of experience in applying machine learning methods towards solving real-world problems. Expert level of understanding of Nautral Language Understanding and Machine learning/Deep learning methods. Experience in artificial intelligence and its practical application to the creation of interactive systems, with specific emphasis in two or more of the following areas:

Sequence tagging.
Intent classification.
Language modeling.
Text prediction.
Active learning.
Minimum Requirements:
Expert-level understanding of Artificial Intelligence technologies including: Machine learning and deep learning methods
Solid knowledge in deep learning algorithms, Advanced Driver Assistance Systems, and the latest architecture for AI.
Development of end to end product based on machine learning
Deep understanding of computer architecture is a plus; knowledge of Computer Vision will be an added advantage.
Excellent understanding of complex system architecture, components and requirements.
Innovation minded, highly capable to think systematically, capable to redefine the solutions to overcome the competitors and solving problems.
Self-driving, energetic, creative and ability to work in international teams.
Curious and willing to challenge existing solutions with innovative technology concepts.
Experience with Knowledge representation and reasoning and related semantic technologies, knowledge modeling/authoring and management, including: Prolog, logic programming, and Rulelog methods; other business rules methods such as production rules, Drools/JBoss, event-condition-action rules.
Desired candidate should be familiar with methods for ontologies, terminologies, graph databases, knowledge graphs (e.g., RDF, SPARQL, OWL), and related information integration; propositional logic, first-order logic, and constraint satisfaction methods; methods for uncertainty in combination with logical methods (e.g., Bayesian, probabilistic soft logic); combination of the foregoing with natural language, e.g., in knowledge authoring/debugging and explanation; combination of the foregoing with machine learning, e.g., in knowledge acquisition.


Minimum: Master’s Degree
Preferred: Doctoral/Professional Degree in Computer Vision, Pattern Recognition or Artificial Intelligence with specialization in Machine learning /Deep learning methodologies
Ph.D. or Degree in Computer Science, operational research Information and Communication Technology (ICT) or related background.
Deep knowledge in artificial intelligence
Record of academic publishing in related conferences and/or journals
Proven and demonstrated implementation skills (putting theory into practice)

Educational level:

Master Degree

Level of experience (years):

Senior (5+ years of experience)

How to apply:

Please mention NLP People as a source when applying


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About Accenture

Accenture is a global management consulting, technology services and outsourcing company, with more than 323,000 people serving clients in more than 120 countries. Combining unparalleled experience, comprehensive capabilities across all industries and business functions, and extensive research on the world’s most successful companies, Accenture collaborates with clients to help them become high-performance businesses and governments. The company generated net revenues of US$30.0 billion for the fiscal year ended Aug. 31, 2014. Its home page is www.accenture.com.