Staff ML Engineer, Applied AI
- Design and implement LLM-powered features using models like Gemini, LLaMA, or lighter BERT variants
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines, vector stores, and embedding systems.
- Fine-tune or adapt foundation models using PEFT techniques to meet the needs of use cases.
- Define and conduct evaluations, address losses, deploy and monitor LLM applications in production.
- Collaborate cross-functionally with product, infra, and domain teams to ship end-to-end solutions.
- Influence technical decisions and roadmap. Guide junior team members
- Stay current with new developments in the LLM technical landscape and help us productionize new capabilities quickly and safely.
- 5+ years of hands on experience in ML with 3+ years of experience as an NLP Engineer
- Strong hands-on experience in developing and deploying applications using a LLM using common tuning methods.
- High proficiency in Python and deep learning libraries
- Experience deploying and monitoring ML systems in production
- Strong product sense and interest in solving customer-facing problems.”
- Collaboration, initiative and motivation to handle ambiguity and progress with design and implementation.
- Fine-tune or adapt foundation models using PEFT techniques to meet the needs of use cases.
- Background in one or more of: NLU/NLG, document understanding, knowledge graphs, or multimodal learning.
- Experience in orchestration frameworks such as LangGraph
- Experience with Voice AI
- Experience as technical lead of an ML team.
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