Data Scientist

2 days ago

Pune, Maharashtra, India Zorba Consulting Full time ₹ 12,00,000 - ₹ 36,00,000 per year

About The Opportunity :

We are a fast-growing enterprise AI & data science consultancy serving global clients across finance, healthcare, and enterprise software.

The team builds production-grade LLM-driven productsRAG systems, intelligent assistants, and custom inference pipelinesthat deliver measurable business outcomes.

Role & Responsibilities :

  • Design, fine-tune and productionize large language models (instruction tuning, LoRA/PEFT) using PyTorch and Hugging Face tooling for real-world applications.

  • Architect and implement RAG pipelines : embeddings generation, chunking strategies, vector search integration (FAISS/Pinecone/Milvus) and relevance tuning for high-quality retrieval.

  • Build scalable inference services and APIs (FastAPI/Falcon), containerize (Docker) and deploy to cloud/Kubernetes with low-latency and cost-optimized inference (quantization, ONNX/Triton).

  • Collaborate with data engineers and ML scientists to productionize data pipelines, automate retraining, monitoring, evaluation and drift detection.

  • Drive prompt-engineering, evaluation frameworks and safety/guardrail implementation to ensure reliable, explainable LLM behavior in production.

  • Establish engineering best-practices (Git workflows, CI/CD, unit tests, observability) and mentor junior engineers to raise team delivery standards.

Skills & Qualifications :

Must-Have :

  • 4+ years in data science/ML engineering with demonstrable experience building and shipping LLM-based solutions to production.

  • Strong Python engineering background and hands-on experience with PyTorch and Hugging Face Transformers (fine-tuning, tokenizers, model optimization).

  • Practical experience implementing RAG : embeddings, vector DBs (FAISS / Pinecone / Weaviate / Milvus) , chunking and retrieval tuning.

  • Production deployment experience : Docker, Kubernetes, cloud infra (AWS/GCP/Azure) and inference optimization (quantization, batching, ONNX/Triton).

Preferred :

  • Experience with LangChain/LangGraph or similar orchestration frameworks, and building agentic workflows.

  • Familiarity with ML observability, model governance, safety/bias mitigation techniques and cost/performance trade-offs for production LLMs.

Benefits & Culture Highlights :

  • Hybrid working model in India with flexible hours, focused on outcomes and work-life balance.

  • Opportunity to work on cutting-edge GenAI engagements for enterprise customers and accelerate your LLM engineering career.

  • Collaborative consultancy culture with mentorship, learning stipend and clear growth paths into technical leadership.

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