Data Scientist - GEN AI

Job Title: Data Scientist (GenAI Expert)

Expereince 6 to 9 years

JR NO - 25507

Bangalore

Job Description:

We are seeking a highly skilled and motivated Data Scientist (GenAI Expert) to join our dynamic team. The ideal candidate will have a strong background in Generative AI, programming, data analysis, statistical methods, machine learning, and big data technologies. You will be responsible for building and fine tuning LLM applications and contributing to data-driven decision-making processes.

Key Responsibilities:

Build and fine-tune large-language-model (LLM) applications, including retrieval-augmented generation (RAG) pipelines, prompt-engineering frameworks, and AI assistants for industrial use-cases.

Develop anomaly-detection, forecasting, and recommendation engines on multivariate time-series and event data.

Implement CI/CD, automated testing, model monitoring, and feedback loops to ensure high availability and performance of GenAI services.

Optimize inference latency, cost, and compliance (security, privacy).

Partner with process engineers, control-system experts, and business stakeholders to translate industrial problems into AI solutions.

Mentor junior engineers and create documentation, demos, and training materials.

Track emerging GenAI techniques (agents, function calling, vector databases) and rapidly prototype proofs of concept.

Contribute reusable components to the organization s AI accelerator catalogue.

Qualifications:

Technical Stack: Python, PyTorch/TensorFlow, LangChain/LlamaIndex, FastAPI/Flask, Azure/GCP/AWS GenAI services, vector databases (Pinecone/FAISS), time-series DBs (OSIsoft PI, Influx, Prometheus),

AI/ML Expertise: Demonstrated success deploying LLMs, RAG, anomaly-detection, causal inference, and recommendation systems.

Data Engineering: Strong skills in building scalable, fault-tolerant data pipelines and streaming analytics.

Industrial Domain Awareness: Understanding of manufacturing KPIs (availability, performance, quality) and control-system architectures.

Education: B.Sc. or higher in Computer Science, Data Science, Industrial Engineering, or related field.