Data Scientist AI/ML (DT80SI RM 3814)

Position: Data Scientist AI/ML (DT80SI RM 3814)

Interview Drive on 19th Dec

Mandatory Skills: AI/ML Data Engineer Building AI Driven system- Primary- AI/ML

• At least 5+ years of experience ML Engineering/MLOps/LLMOps (must)
• Strong foundation in LLM operations — prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).
• Hands-on experience with frameworks like LangChain, LlamaIndex, Hugging Face, or similar orchestration tools.
• Proven ability to design and deploy on Azure Cloud (experience with AWS or GCP also valuable).
• Relevant in Python- 5 years
  

What You’ll Do

• Architect and deliver end-to-end AI solutions, from model design and RAG pipelines to scalable APIs and microservices.
• Build and deploy agentic AI systems that enable autonomous task orchestration and reasoning. Lead efforts to operationalize LLMs, including safety guardrails, evaluation pipelines, and performance monitoring.
• Collaborate with product, data, and cloud teams to integrate AI capabilities into production environments.
• Mentor engineers and set technical direction for AI development standards and best practices.
  

What You’ll Bring

• 10+ years of software engineering experience, including deep expertise in Python and production-grade ML/AI systems.
• Atleast 5+ years of experience ML Engineering/MLOps/LLMOps (must)
• Strong foundation in LLM operations — prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).
• Hands-on experience with frameworks like LangChain, LlamaIndex, Hugging Face, or similar orchestration tools.
• Proven ability to design and deploy on Azure Cloud (experience with AWS or GCP also valuable).
• Solid understanding of DevOps principles — CI/CD, containerization (Docker), and GitOps workflows.
• Experience delivering reliable, well-tested, and maintainable code in agile environments.
• Excellent communication skills and a collaborative, problem-solving mindset.
  

Nice to Have

• Familiarity with Databricks and/or Snowflake.
• Understanding of enterprise-grade security (OAuth, OIDC, SSO).
• Experience with TDD, observability tools (e.g., New Relic, Splunk), and structured documentation (OpenAPI).