
Data Scientist-LLM Engineer_4+yrs
2 weeks ago
Primary Role Title: Senior LLM Engineer
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.
Location: India (Hybrid)
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.
This role is with Zorba Consulting India. If you are an experienced LLM practitioner who enjoys end-to-end ownershipfrom research experiments to robust production systemsapply with your resume and a short note on a recent LLM project you led (models, infra, and outcomes).
Zorba Consulting India is an equal opportunity employer committed to diversity and inclusion.
Skills: ml,llm,data science
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