LLM Expert
3 days ago
Senior Large Language Model Engineer
About the Role :
We are a fast-growing enterprise AI consultancy serving global clients across finance, healthcare, and enterprise software.
The team builds production-grade LLM-driven products and systems that deliver measurable business outcomes.
Key Responsibilities :
- Design, fine-tune, and productionize large language models using PyTorch and Hugging Face tooling for real-world applications.
- Architect and implement Retrieval-Augmented Generation (RAG) pipelines : embeddings generation, chunking strategies, vector search integration, and relevance tuning for high-quality retrieval.
- Build scalable inference services and APIs, containerize, and deploy to cloud/Kubernetes with low-latency and cost-optimized inference.
- 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 and mentor junior engineers to raise team delivery standards.
Mandatory Skills :
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.
- Practical experience implementing RAG : embeddings, vector DBs, and chunking and retrieval tuning.
- Production deployment experience : Docker, Kubernetes, cloud infra, and inference optimization.
Desirable :
- 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.
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