Location- Gurugram
Experience- 2-3 years

Strong software engineering fundamentals in Python — including writing clean, modular, testable code and designing maintainable codebases/architectures, not just scripting models
Proven experience building and deploying ML/GenAI solutions end-to-end — from model/prompt design through to production deployment, using frameworks such as scikit-learn, TensorFlow, or PyTorch
Deep knowledge of LLMs and generative AI , including prompt engineering, retrieval-augmented generation (RAG), embeddings, and vector databases
Experience designing and building AI agents and automation workflows (not just calling APIs — architecting multi-step, tool-using systems)
Backend and API development experience , with the ability to integrate AI models cleanly into existing products and services
Cloud platform experience (Azure and/or AWS) and comfort deploying containerized workloads (Docker/Kubernetes) at scale
Solid grasp of the full ML lifecycle : data preprocessing, model evaluation, monitoring, and deployment — with an eye toward reliability and scalability in production, not just notebook experimentation
Git and standard version control practices

Strongly Preferred




Familiarity with MLOps tooling and practices (CI/CD for ML, model versioning, monitoring/observability)
Experience with data pipelines and ETL processes, and working with both structured and unstructured data
Understanding of responsible AI, privacy, and security practices in AI systems
Experience with MCP (Model Context Protocol) tools or similar emerging agent-tooling standards

What You'll Do
Architect and build AI-powered applications and services designed to scale beyond a proof of concept
Fine-tune and productionize ML/GenAI models, integrating them into existing products, workflows, and APIs
Design retrieval-augmented generation and agent-based workflows for real business use cases
Make sound engineering trade-offs on system design, performance, and maintainability as usage grows

Soft Skills
Strong problem-solving and communication skills; able to explain technical trade-offs to non-technical stakeholders
Comfortable owning ambiguous problems and working independently in a fast-paced workplace
Collaborative — works well across engineering, data science, and product teams

📌 Data Science - Administrator (Gurugram)
🏢 Marsh
📍 Gurugram