Location- Gurugram

nExperience- 2-3 years

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- Strong software engineering fundamentals in Python — including writing clean, modular, testable code and designing maintainable codebases/architectures, not just scripting models
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- 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
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- Deep knowledge of LLMs and generative AI, including prompt engineering, retrieval-augmented generation (RAG), embeddings, and vector databases
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- Experience designing and building AI agents and automation workflows (not just calling APIs — architecting multi-step, tool-using systems)
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- Backend and API development experience, with the ability to integrate AI models cleanly into existing products and services
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- Cloud platform experience (Azure and/or AWS) and comfort deploying containerized workloads (Docker/Kubernetes) at scale
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- 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
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- Git and standard version control practices
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nStrongly Preferred

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

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

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- Strong problem-solving and communication skills; able to explain technical trade-offs to non-technical stakeholders
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- Comfortable owning ambiguous problems and working independently in a fast-paced environment
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- Team-oriented — works well across engineering, data science, and product teams
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📌 Data Science - Administrator (Gurugram)
🏢 Marsh
📍 Gurugram