Senior Machine Learning (ML) Engineer

Responsibilities

• Design and build multi-agent AI workflows with reasoning, planning, memory, and goal-driven behavior.
• Develop and integrate embeddings, vector stores, retrieval-augmented generation, and semantic-search pipelines.
• Fine-tune and optimize large language and multimodal models using supervised, reinforcement, or instruction-tuning techniques.
• Design scalable, maintainable software systems that integrate into large-scale AI platforms.
• Create evaluation methods, reward functions, evaluators, and grader models for reinforcement fine-tuning and continuous improvement.
• Collaborate with platform, application, and product engineers to deliver reliable AI solutions.
• Set technical direction, mentor peers, and make pragmatic design trade-offs.
• Apply ethical AI and thoughtful engineering practices to healthcare intelligence systems.

Requirements

• At least 5 years of experience building and deploying scalable, production-ready machine learning systems.
• Proficiency with LangGraph, AutoGen, or CrewAI and familiarity with MCP and A2A interoperability protocols.
• Hands-on experience fine-tuning and optimizing LLMs or multimodal models using LoRA, PEFT, or TRL.
• Experience integrating FAISS, Pinecone, Chroma, Azure AI Search, or similar vector databases into retrieval or semantic-search pipelines.
• Strong software engineering fundamentals and proficiency with Python.
• Experience designing scalable systems in modern cloud environments such as Azure, AWS, or GCP.
• Bachelor’s or master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
• Knowledge of transformer architectures, attention mechanisms, tokenization, embeddings, context windows, model scaling, ML validation, and evaluation metrics.
• Experience with technical ownership, cross-functional collaboration, mentoring, and responsible AI engineering.

Benefits

• Comprehensive medical, dental, and vision insurance.
• 401(k) plan.
• Professional development and training opportunities.
• Flexible work hours and flexible paid time off.
• Generous parental leave.
• Regular virtual and in-person team activities.
• Hybrid work arrangement based at headquarters in the Greater Seattle area.
• Eligible roles may receive incentive pay and stock options.
• Applicants must be authorized to work in the United States; visa sponsorship is unavailable.