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Key Responsibilities :

Python Engineering & System Development :

- Develop robust, scalable AI/ML applications using Python.
- Build modular, production-ready code following strong software engineering practices (testing, linting, packaging, version control).
- Develop and maintain APIs using FastAPI, Flask, or similar frameworks.
- Debug and optimize deployed systems across backend services, APIs, frontend integrations, and cloud dependencies.

AI/ML & GenAI Development :

- Lead data discovery, feature engineering, experimentation, and model development.
- Work across classical ML, deep learning, and NLP/LLM-based systems (embeddings, fine-tuning, RAG).
- Design rigorous evaluation strategies including offline metrics, regression testing, failure-mode analysis, and human-in-the-loop validation for GenAI systems.
- Ensure model reproducibility, documentation, versioning, and traceability.

Deployment Pipelines & DevOps :

- Build and manage CI/CD pipelines for ML and AI workflows.
- Containerize applications using Docker and deploy via Kubernetes (preferred).
- Implement DevOps, MLOps, and LLMOps best practices.
- Manage release cycles, change controls, and environment configurations.
- Ensure secure API integrations and scalable inference pipelines.





Cloud & Client Environment Deployment :

- Deploy AI/ML solutions on Microsoft Azure (Function Apps, scaling, integrations).
- Manage configuration, monitoring, and performance optimization in live environments.
- Support deployments within client-controlled infrastructures.
- Work within client security, access control, and infrastructure constraints.
- Own end-to-end troubleshooting and incident management in production systems.

Technical Requirements :

- Robust proficiency in Python and ML/DS libraries (Pandas, scikit-learn, PyTorch/TensorFlow, XGBoost/LightGBM).
- Strong SQL and data wrangling skills; experience with Spark/Databricks is a plus.
- Hands-on experience with API-based deployments and cloud-native architectures.
- Experience with CI/CD tools, containerization, and orchestration frameworks.
- Familiarity with LLM orchestration tools (Langgraph, Langflow, Flowise) is a plus.

Soft Skills :

- Strong cross-functional collaboration skills.
- Ability to communicate technical solutions clearly to both technical and non-technical stakeholders.
- High ownership mindset with full lifecycle accountability.

📌 Data Scientist - AI/ML (India)
🏢 Its All About People (ITAAP)
📍 India