Ai Ml Engineer

Required Skills & Qualifications:

Must-Have (Non-Negotiable)

• 2 to 8 years of hands-on experience in ML, AI, or applied data science
• Strong Python and at least one DL framework (PyTorch / TensorFlow / JAX)
• Real production experience with LLMs prompt engineering, fine-tuning, RAG, agent

frameworks (LangChain, LangGraph, CrewAI, or custom)

• Solid grounding in classical ML (regression, trees, ensembles) and modern DL

(transformers, vision, time-series)

• PostgreSQL + vector DBs (pgvector / Pinecone / Qdrant / Weaviate) and pipeline tools

(Airflow, Prefect, or similar)

• Proficiency with AI coding assistants (Claude Code, Cursor, Copilot) — used daily for 2–3x

velocity

• Git, Docker, basic AWS/cloud deployment, and ability to ship features end-to-end

Strongly Preferred

• Experience in healthtech, infra/construction tech, geospatial/CV, or voice AI
• Edge AI / on-device inference experience: TFLite, ONNX Runtime Mobile, CoreML,

MediaPipe, NVIDIA Jetson, or similar

• Hands-on with open-source LLMs — fine-tuning (LoRA/QLoRA), quantization (GGUF,

AWQ, GPTQ), and serving (vLLM, Ollama, TGI, llama.cpp)

• Knowledge graphs (Neo4j), graph ML, or causal inference
• Computer vision experience (YOLO, SAM, detection/segmentation, OCR)
• Experience with Sarvam AI, Bhashini, or Indic language models
• Time-series forecasting (Prophet, XGBoost, deep forecasting)
• MLOps tooling: MLflow, Weights & Biases, Kubeflow, SageMaker
• Microservices, FastAPI, event-driven architecture (Kafka)

Nice-to-Have

• Open-source contributions, research papers, or public AI projects
• Prior founding-team or 01 product experience
• Domain exposure: clinical workflows, BIM/IFC, BOQ/EVM, road asset standards
• Model serving with ONNX Runtime, Triton, or vLLM