Key Responsibilities

Technical Leadership

- Lead end-to-end design and development of AI/ML and GenAI-based solutions

- Define system architecture for scalable, secure, and high-performance Python applications

- Review code, enforce best practices, and ensure high-quality deliverables

- Mentor and guide junior developers and ML engineers

Machine Learning & GenAI

- Design, train, and deploy ML and deep learning models

- Build Generative AI solutions using LLMs (GPT, Claude, LLaMA, Mistral, etc.)

- Implement RAG (Retrieval-Augmented Generation) pipelines using vector databases

- Fine-tune LLMs using LoRA / PEFT / RLHF techniques

- Apply NLP, computer vision, or recommendation algorithms as needed

Backend & MLOps

- Develop REST/GraphQL APIs using FastAPI / Flask / Django

- Implement MLOps pipelines for model training, versioning, and deployment

- Work with Docker, Kubernetes, and CI/CD pipelines

- Monitor model performance, drift, and system reliability in production

Data & Cloud

- Collaborate with data engineers on data pipelines and feature engineering

- Work with cloud platforms: AWS / Azure / GCP

- Integrate with databases: PostgreSQL, MongoDB, Redis

- Use vector databases: Pinecone, FAISS, Weaviate, Milvus

Required Skills

Core Technical Skills

- Expert-level Python (OOP, async, performance optimization)

- Strong understanding of data structures, algorithms, and system design

- Hands-on experience with FastAPI / Flask / Django

Machine Learning & GenAI

- Solid experience with scikit-learn, TensorFlow, PyTorch

- Strong NLP fundamentals (transformers, embeddings, tokenization)

- Experience with LangChain / LlamaIndex / Semantic Kernel

- Prompt engineering and LLM evaluation techniques

Education

- Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field

- Relevant certifications in AI/ML or Cloud are a plus

Experience

- 7+ Years