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Truveta · 1 day ago

Senior Machine Learning Engineer

Greater Seattle Area

Full-time

Onsite

Senior Level

$165K/yr - $190K/yr

5+ years exp

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. The Senior Machine Learning Engineer will engineer adaptive agentic systems and fine-tuned foundation models to transform health data into actionable intelligence, driving impactful decisions in healthcare.

AnalyticsData ManagementHealth Care

No H1B

U.S. Citizen Only

Responsibilities

Design and reason with agentic AI frameworks — experienced in building multi-agent workflows using frameworks such as LangGraph, AutoGen, or CrewAI, integrating reasoning, planning, and memory to create intelligent, goal-driven systems

Bring a deep understanding of LLM fundamentals — knowledgeable in transformer architectures, attention mechanisms, and tokenization principles. You understand how embeddings, context windows, and model scaling laws influence quality, cost, and performance

Work fluently with embeddings and vector stores — experienced in building or integrating retrieval-augmented generation (RAG) pipelines, managing vector databases (e.g., FAISS, Pinecone, Chroma, Azure AI Search, or similar), and leveraging semantic search or context injection to enhance reasoning

Excel at model fine-tuning — with hands-on expertise fine-tuning large language models (LLMs) or multimodal models using supervised, reinforcement, or instruction-tuning techniques (e.g., LoRA, PEFT, TRL). Skilled at optimizing model efficiency, interpretability, and inference performance

Think and build like engineers — grounded in strong software design principles, modular architecture, and code quality. You can translate experimental ideas into robust, maintainable systems that integrate seamlessly within large-scale AI platforms

Collaborate across boundaries — partnering with platform, application, and product engineers to transform concepts into scalable, reliable AI solutions. You communicate clearly, share knowledge openly, and thrive in cross-functional teams

Demonstrate senior-level ownership — capable of setting technical direction, mentoring peers, and making pragmatic design trade-offs that balance innovation, performance, and reliability

Understand evaluation deeply — fluent in ML validation and measurement (Precision, Recall, Specificity, NPV, etc.), and experienced designing reward functions, evaluators, or grader models for reinforcement fine-tuning and continuous improvement

Adapt and learn continuously — staying ahead of evolving AI architectures, agentic frameworks, and emerging paradigms in reasoning and retrieval. You have curiosity, humility, and a bias for iteration

Act with purpose — applying thoughtful engineering and ethical AI principles to create systems that advance healthcare intelligence responsibly and at scale

Qualification

Agentic AI frameworksLarge language modelsVector databasesModel fine-tuningPythonCloud environmentsEthical AI principlesCollaborationContinuous learning

Required

5+ years of experience building and deploying scalable, production-ready ML systems in a collaborative engineering environment

Proficiency with agentic AI frameworks (e.g., LangGraph, AutoGen, CrewAI) and understanding of interoperability protocols such as MCP and A2A

Hands-on experience fine-tuning and optimizing large language models (LLMs) or multimodal models, using techniques such as LoRA, PEFT, and TRL

Experience working with vector databases and embeddings, integrating FAISS, Pinecone, Chroma, or Azure AI Search into retrieval-augmented generation (RAG) or semantic-search pipelines

Strong software engineering fundamentals, with proficiency in Python and experience designing scalable systems in modern cloud environments (Azure, AWS, or GCP)

B.S. or M.S. in Computer Science, Artificial Intelligence, or a related technical field