AI/ML Engineer

About the Role

We are looking for a Senior AI/ML Engineer who combines strong machine learning fundamentals with hands-on experience taking AI systems from proof of concept to production. You will design, build, evaluate, and operate ML and GenAI solutions, including LLM-powered applications, RAG pipelines, and agentic workflows, that run reliably at scale inside real enterprise environments.

This is not a role for someone whose experience is limited to calling third-party LLM APIs, writing prompts, or assembling simple chatbots with off-the-shelf frameworks. We want engineers who understand what happens beneath the abstractions and can own a solution end to end.

Key Responsibilities

• Design, train, tune, and evaluate ML/DL models for classification, regression, recommendation, anomaly detection, predictive analytics, and NLP use cases
• Build data preprocessing and feature engineering pipelines
• Take AI/ML solutions from POC to production, including optimization, monitoring, and troubleshooting
• Build and maintain ground-truth and benchmark datasets, and select appropriate evaluation metrics
• Evaluate LLM and AI systems on accuracy, relevance, groundedness, hallucination, consistency, and task completion
• Develop RAG systems using embeddings, vector databases, retrieval strategies, and reranking
• Implement structured outputs and function/tool calling with LLMs (API-based and open-source)
• Build agentic workflows covering planning, task decomposition, tool execution, state, memory, and context management
• Implement guardrails, validation, retries, fallbacks, and human-in-the-loop controls
• Translate HLD/LLD documents into working, maintainable implementations
• Design scalable, secure AI systems that integrate LLMs, agents, APIs, databases, vector stores, and enterprise systems
• Build backend services and REST APIs with authentication, validation, logging, and error handling
• Optimize inference and system performance using caching, queues, batching, and async processing
• Collaborate with product, data, and engineering teams, and contribute to code reviews and technical best practices

Required Skills & Qualifications

Experience: 3–4 years of hands-on experience in AI/ML engineering, with demonstrated production deployments

Core AI/ML

• Strong ML/DL fundamentals, including data preprocessing, feature engineering, model development, training, tuning, and evaluation
• Practical experience across classification, regression, recommendation, anomaly detection, predictive analytics, and NLP

Production AI/ML & Evaluation

• Proven experience moving models from POC to production
• Model monitoring, optimization, and troubleshooting
• Experience with benchmark datasets and LLM evaluation (hallucination, groundedness, relevance, consistency)

GenAI / LLM / RAG

• Experience with LLM APIs and open-source models, prompt engineering, embeddings, vector databases, retrieval, and reranking
• Hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, or equivalent frameworks

Agentic AI

• Experience building AI agents and multi-step agentic workflows
• Understanding of memory, state, tool use, and failure handling in agents

Python & Backend

• Strong Python, OOP, and software engineering fundamentals
• Experience with FastAPI, Flask, or Django; REST APIs; async and background processing

Cloud & Scalability

• Experience with Docker and at least one cloud platform (AWS, Azure, or GCP)
• Familiarity with caching, queues, batching, and production monitoring

Good to Have

• Kubernetes
• CI/CD pipelines
• MLOps tooling and practices (model registry, experiment tracking, automated retraining)

What We Expect From a Senior Engineer

• Strong underlying AI/ML capability, not just framework-level knowledge
• Practical, demonstrable production experience
• Ability to reason about trade-offs in architecture, cost, latency, and quality
• Ownership of solutions from design through deployment and monitoring

Pay: ₹410,000.00 - ₹960,000.00 per year

Benefits:

• Health insurance
• Paid time off
• Provident Fund

Work Location: In person