Senior Engineer Consultant-AI Science

3 - 7 years

15 - 20 Lacs

Posted:9 months ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

As Sr. Engineer Consultant - AI Science you will design, develop and optimize Artificial Intelligence, SLM/LLM solutions to diverse real-world problems and implement cutting-edge generative artificial intelligence models and systems. This role includes a combination of implementing new algorithms, SLM/LLMs, performance/accuracy tuning and analysis, defining APIs, and analyzing functionality coverage to build larger, coherent toolsets and libraries. The ability to work in a multifaceted, product-centric environment with excellent interpersonal skills.

  • Leading the design, development, and implementation of end-to-end NLP/SLM/LLM solutions using Python, Pyspark, distributed computing framework and cloud platform.
  • Driving Cognitive AI use cases with cross-functional teams delivering business value
  • Data mining or extracting usable data from valuable data sources using SQL.
  • Ability to convert vision into strategy and create an execution plan
  • Contributing to the research and development of novel generative models, exploring new algorithms and methodologies.
  • Developing end to end analytical solutions, and articulating insight findings to leadership. Provide data-driven recommendations to business by clearly articulating complex modeling concepts through generation and delivery of presentations.
  • Identifying and defining new process improvement and or business opportunities.
  • Working in collaborative environment with global teams to drive AI solutioning of business problems
  • Mentoring and guiding junior engineers, fostering a collaborative and innovative team environment.
  • Working closely with management to prioritize business and information needs.

What we are looking for: -

Youll need to have:

  • Bachelors degree or four or more years of work experience.
  • Four or more years of relevant work experience.
  • Four or more years of experience in cognitive analytics and AI modeling.
  • Experience working in collaborative environment with global teams to drive AI solutioning of business problems and implement highly optimized AI algorithms.
  • Experience in large-scale distributed systems capable of performing end-to-end AI training and SLM & LLM modeling includes orchestration, fine tuning, model serving in production environment (batch/real time).
  • Ability to communicate complex model designs and outcomes in business terms to a non-technical audience.
  • Knowledge of GPU/CPU architecture and distributed computing
  • Working knowledge in advance Prompt engineering and optimizations techniques
  • Exposure to large-scale AI training, understanding of the compute system concepts (latency/throughput bottlenecks, pipelining, multiprocessing etc) and related performance analysis and tuning
  • Experience in Research and Development: Stay up-to-date with the latest advancements in generative AI, deep learning, and related fields. Contribute to the research and development of novel generative models, exploring new algorithms and methodologies.
  • Understanding and ability to explain both the code and the underlying math used in algorithms/models. Proficiency in programming languages such as C/C++, Python, Java, debugging, performance analysis and relevant AI libraries/frameworks (TensorFlow, PyTorch, etc.)

Even better if you have :

  • Advance degree in computer science, Mathematics, Data science or related field.
  • Prior experience with Generative AI techniques applied to Large Language Models And multimodal learning (Image, Video, Speech etc.). Advance knowledge of mathematics, Statistics and algorithms.
  • Experience in GCP/Azure/AWS or any other cloud technology. Hands-on experience with inference and deployment environments would be an asset
  • Experience in Research, prototype, and develop effective tools and infrastructure pipelines
  • Publish innovative results on Github, scientific publications and patents.
  • Familiarity with telecommunications industry data and use cases.

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