Senior AI/ML Engineer • Generative AI, NLP, MLOps
Seasoned AI engineer with 12+ years of experience building and shipping production ML and GenAI systems across healthcare, telecom, and insurance. Comfortable owning the full lifecycle from problem framing and data engineering to model design, evaluation, and deployment on cloud-native stacks.
- Senior AI / ML Engineer currently building GenAI applications in healthcare at M42 Health, Abu Dhabi.
- Strong focus on LLM-powered products: RAG, multi-agent workflows, model fine-tuning, and production-grade evaluation.
- Enjoy working at the intersection of data, product, and engineering to deliver measurable business impact, not just models.
- GenAI & NLP: LLMs, SLMs, prompt engineering, fine-tuning, RAG, transformers, LangGraph, LangChain, Langfuse.
- Multimodal & Speech: ASR, text-to-speech, vision-language models for real products like contact center AI and physician assistants.
- Applied ML: Classical ML (XGBoost, Random Forest, SVM), experimentation, and model interpretability for churn, lead scoring, and analytics.
- Systems & MLOps: Python, FastAPI/Django/Flask, microservices, Docker, Kubernetes, Azure, AWS, Databricks, CI/CD for ML.
- Data platforms: SQL, MongoDB, Elasticsearch, Milvus, FAISS, Azure AI Search, Neo4j, Power BI.
- Built an AI-powered analytics platform that turns natural language questions into dynamic SQL and visualizations for clinical and environmental datasets using LLMs, RAG, and MCP.
- Developed a physician-facing chat interface over EHR data using a multi-agent framework and RAG on FHIR-formatted records to support faster, more informed decision-making.
- Created an AI-assisted genetic variant pathogenicity classifier that autonomously pulls and interprets scientific literature and bioinformatics data, reducing analysis time by ~4 hours per patient.
- Led AI for telecom contact centers at Airtel Digital: ASR- and LLM-powered monitoring, lead mining on 200k+ daily calls, and chatbots that increased intent coverage by 16% and improved lead conversion by 10%.
- Drove analytics for Microsoft Surface devices, mining telemetry, app usage, and social media to surface product insights and high-impact issues.
- Built NLP and feedback systems at Info Edge (Shiksha.com) to power virtual agents and insights for universities and students.
- Languages: Python, C, Java
- ML / Data: PyTorch, PySpark, Pandas, scikit-learn, Statsmodels, Databricks
- GenAI: OpenAI / Azure OpenAI APIs, LangChain, LangGraph, Langfuse, RAG tooling
- MLOps & Cloud: AWS, Azure, Docker, Kubernetes, GitHub, Azure ML, Azure AI Foundry
- Datastores: SQL, MongoDB, Elasticsearch, Milvus, FAISS, Azure AI Search, Neo4j
- B.Tech in Chemical Engineering from IIT Kanpur (CGPA 8.2/10).
- Over a decade of experience moving from data analytics and classical ML into large-scale GenAI systems.
Open to discussions on LLM product architectures, healthcare AI, and building robust ML platforms in real-world environments.