Drive Health
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Staff ML Engineer, Applied AI
role at
Drive Health Join to apply for the
Staff ML Engineer, Applied AI
role at
Drive Health Get AI-powered advice on this job and more exclusive features. 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.
Description
What You’ll Do
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.
Requirements
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.
Bonus Points
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. Seniority level
Seniority level Mid-Senior level Employment type
Employment type Full-time Job function
Job function Engineering and Information Technology Industries Public Health Referrals increase your chances of interviewing at Drive Health by 2x Sign in to set job alerts for “Machine Learning Engineer” roles.
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Staff ML Engineer, Applied AI
role at
Drive Health Join to apply for the
Staff ML Engineer, Applied AI
role at
Drive Health Get AI-powered advice on this job and more exclusive features. 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.
Description
What You’ll Do
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.
Requirements
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.
Bonus Points
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. Seniority level
Seniority level Mid-Senior level Employment type
Employment type Full-time Job function
Job function Engineering and Information Technology Industries Public Health Referrals increase your chances of interviewing at Drive Health by 2x Sign in to set job alerts for “Machine Learning Engineer” roles.
Scottsdale, AZ $94,000.00-$150,000.00 1 day ago Python and Kubernetes Software Engineer - Data, AI/ML & Analytics
Scottsdale, AZ $105,000.00-$147,000.00 1 month ago Phoenix, AZ $102,000.00-$129,000.00 3 days ago Advanced Software Engineer – Developer
Python Software Engineer - Ubuntu Hardware Certification Team
Graduate Software Engineer, Open Source and Linux, Canonical Ubuntu
Software Engineer, Ceph & Distributed Storage
Greater Phoenix Area $120,000.00-$162,500.00 2 weeks ago Distributed Systems Software Engineer, Python / Go
Senior Software Engineer, Backend (ML Platform)
Software Engineer - Cross-platform C++ - Multipass
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We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr