Lead Data Science Engineer

1 week ago

Hyderabad Noida, India S&P Global Market Intelligence Full time ₹ 20,00,000 - ₹ 25,00,000 per year

We are seeking a highly skilled and motivated AI/ML Engineer Lead to join our team. The ideal candidate will have a strong background in machine learning and data science, with experience working on large-scale machine learning projects. As a Machine Learning Engineer, you will be responsible for designing, implementing, and optimizing machine learning models and algorithms to solve complex business problems. You will work closely with cross-functional teams, including data scientists, software engineers, and product managers, to develop innovative solutions that drive business growth.

Requirements:

  • Bachelors or masters degree in computer science, Data Science , or a related technical discipline.
  • Total 10+ years ofoverall all software developmentexperience with 3+ years of hands-on experience in machine learning or AI application development , with a proven track record of delivering production-grade solutions.
  • Strong programming proficiency in Python , with demonstrated experience in API development using FastAPI or Flask .
  • Backend development experience in C# or Java is considered an added advantage.
  • Solidexperience in developing AI solutions within the AWS ecosystem , including hands-on use of the following services: Amazon Bedrock , SageMaker , Lambda , API Gateway , and S3 etc.
  • Practical knowledge and implementation experience with Large Language Models (LLMs) and Generative AI frameworks , such as: LangChain , Llama Index , or custom RAG (Retrieval-Augmented Generation) architectures.
  • In-depth understanding of RAG systems , including embedding generation, document chunking, retrieval, and response synthesis.
  • Experience with vector databases (e.g., Pinecone, FAISS, OpenSearch), text embeddings , and prompt engineering is added advantage.
  • Strong understanding of cloud security , including OAuth 2.0-based authentication , IAM policies , and secure API design.
  • Familiarity with DevOps practices and tools, including CI/CD pipelines , Docker , and Infrastructure as Code (IaC) tools such as CloudFormation , AWS CDK , or Terraform .
  • Proficiency in relational databases (e.g., SQL) and data modelling.
  • Solid grasp of machine learning algorithms and techniques , including deep learning architectures.
  • Skilled in data preprocessing , feature engineering , and data manipulation using modern data science tools and libraries.
  • Demonstrated experience working across the full AI/ML project lifecycle from business requirements analysis to model deployment and productization.
  • Strong analytical and problem-solving skills , with a structured approach to debugging and optimization.
  • Excellent communication and collaboration abilities , with experience working in cross-functional and agile teams.

People Sills

  • Able to translate business problems into problems that can be solved with Data Science
  • Able to communicate technical ideas effectively to non-technical audience
  • Ability to work in a team
  • Curious and open-minded attitude to new approaches

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