AI Engineer

Design, build, and deploy AI/ML systems that power products and automate workflows. Own models end-to-end—from data to production.

 

• Develop and train ML/DL models (NLP, CV, or tabular)

• Build data pipelines and feature engineering workflows

• Deploy models via APIs/microservices (cloud or on-prem)

• Integrate AI into products and existing systems

• Monitor model performance, drift, and reliability

• Optimize models for scale, latency, and cost

• Collaborate with product, engineering, and domain teams

 

• Strong Python (NumPy, Pandas, PyTorch/TensorFlow, scikit-learn)

• Solid ML fundamentals (supervised/unsupervised, evaluation, tuning)

• Experience with LLMs, prompt engineering, or fine-tuning (preferred)

• API development (FastAPI/Flask) and microservices

• Cloud platforms: AWS / Azure / Google Cloud Platform

• Data handling (SQL, ETL, large datasets)

• Versioning & MLOps (Git, Docker, CI/CD, MLflow)

 

MCP(Model context protocol) , A2A (Agent to Agent) etc is also required to show the depth