Generative AI Engineer - Data Modeling

Job Title : Generative AI / Machine Learning Engineer

Location : Pune, India

Experience Required : 7+ years

Notice Period : Immediate / Serving Notice

About the Role :

Key Responsibilities :

Model Development & Deployment :

- Design, train, and deploy supervised and unsupervised ML models for large-scale

applications.

- Build and optimize Generative AI pipelines (LLMs, RAG architectures, AI Agents).

- Implement scalable data preprocessing, feature engineering, and inference workflows.

Generative AI Applications :

- Architect and implement RAG pipelines combining vector databases (e.g., Pinecone, Weaviate, FAISS) and LLMs for enterprise knowledge retrieval.

- Build and deploy AI Agents for automation, decision support, and conversational systems.

Engineering & Integration :

- Write clean, production-grade Python code following best practices.

- Collaborate with data engineers, product managers, and DevOps teams to deliver scalable AI solutions.

MLOps & Cloud :

- Use MLOps frameworks (MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML) for experiment tracking, CI/CD, and deployment.

- Optimize models for latency, scalability, and cost efficiency.

Required Skills & Qualifications :

Technical Expertise :

- Strong proficiency in Python and ML libraries : TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers.

- Deep understanding of ML algorithms (supervised, unsupervised, deep learning).

- Proven hands-on experience in Generative AI frameworks (LangChain, LlamaIndex, Haystack, RAG pipelines, AI Agent frameworks).

Applied Knowledge :

- Experience with vector databases (Pinecone, FAISS, Weaviate, Milvus).

- Strong foundation in data preprocessing, feature engineering, and model evaluation.

Bonus Skills :

- MLOps exposure (CI/CD pipelines, model monitoring, drift detection).

- Cloud experience with AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure ML.

- Familiarity with API design, microservices architecture, and distributed systems.

Education :

- Bachelors or Masters in Computer Science, Data Science, AI/ML, or related fields.