
Principal Language Model Engineer
2 weeks ago
Job Opportunity:
- Develop large-scale language models for real-world applications using PyTorch and Hugging Face tooling.
- Design and implement RAG pipelines : embeddings generation, chunking strategies, vector search integration and relevance tuning.
- Build scalable inference services and APIs, containerize and deploy to cloud/Kubernetes with low-latency and cost-optimized inference.
- Collaborate on data pipelines, automate retraining, monitoring, evaluation and drift detection.
- Implement prompt-engineering, evaluation frameworks and safety/guardrails to ensure reliable LLM behavior.
- Establish engineering best-practices and mentor junior engineers to raise team delivery standards.
Requirements:
- 4+ years in data science/ML engineering with experience building and shipping LLM-based solutions.
- Strong Python background and hands-on experience with PyTorch and Hugging Face Transformers.
- Practical experience implementing RAG : embeddings, vector DBs, chunking and retrieval tuning.
- Production deployment experience : Docker, Kubernetes, cloud infra and inference optimization.
Preferred:
- Experience with LangChain/LangGraph or similar orchestration frameworks.
- Familiarity with ML observability, model governance, safety/bias mitigation techniques and cost/performance trade-offs.
About the Role:
Join a fast-growing enterprise AI & data science consultancy serving global clients across finance, healthcare and enterprise software.
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