Staff Machine Learning Engineer

📋 Job Overview

Plenful is on a mission to transform healthcare operations from the inside out. Fresh off our $50M Series B and backed by Notable Capital, Bessemer Venture Partners, TQ Ventures, Susa/Kivu Ventures, and other leading investors, we’re building the category-defining AI automation platform that healthcare teams rely on to operate smarter, faster, and more efficiently. Our technology empowers healthcare operators across hospital and health systems, pharmacies and payors to eliminate manual work, reduce administrative burden, and improve compliance, all while unlocking critical revenue to fund programs for their in-need patient populations.

🏢 About Plenful

Built by healthcare operators for healthcare operators, Plenful is driven by a deep understanding of the challenges facing today’s care teams. We’re passionate about equipping healthcare workers with world-class tools that deliver real, measurable impact, and we’re proud to serve 100+ leading health systems, pharmacies, and healthcare organizations across the country. If you’re excited to help shape the future of healthcare, we’d love to meet you.

🎯 The Role

Healthcare's back office still runs on faxes, PDFs and phone calls. AI can take that work off people's plates, but only if it is accurate enough to trust with patient and financial data. At Plenful, we build agents and models that do that work in production, with people in the loop wherever judgment matters. As a Staff Machine Learning Engineer, you set the technical direction for how we build, train and measure AI across the company, and you stay hands-on while you do it. This is an individual contributor role with no direct reports and broad influence.

✅ Key Responsibilities

• You set the direction for how our agents are built
• You own our post-training strategy
• You define what good looks like
• You build loops that improve themselves
• You raise the bar for everyone

📌 Required Qualifications

• 8+ years in ML or software engineering, including 3+ years leading LLM or agentic systems in production.
• Deep applied post-training experience. You have run supervised fine-tuning, preference optimization, distillation or RL end to end and shipped a model that moved a production metric.
• You have designed an evaluation strategy for LLM or agent systems and seen it drive real release decisions.
• You have architected production agent systems and can name what broke and what you changed. Experience with frameworks like LangGraph, RAG and vector search (for example Pinecone) is expected.
• Strong Python and PyTorch, and comfort with distributed training and serving (for example vLLM, FSDP or DeepSpeed).
• Real MLOps depth: Docker, Kubernetes, MLflow or equivalent, CI/CD, and experiment and dataset tracking.
• You influence without authority. Your design docs, reviews and mentoring make other engineers better.
• You stay current, and others rely on it
• You use new models and coding agents the week they ship, and colleagues ask you whether a new thing is real.
• You turn papers and releases into experiments within days and report back with numbers.
• You have proof: open source, write-ups, talks, or evals other people use.

⭐ Desirable Experience

• Healthcare data experience: EHR, FHIR, claims, prior authorization.
• Publications or open-source work in LLM evaluation, post-training or agents.
• Experience interviewing and hiring ML engineers.
• Work in another regulated, high-stakes domain.

🎁 Benefits

• Healthcare Coverage — Full medical, dental, and vision insurance for you and participation for your family
• 401(k) with Company Match — Plenful matches 50% of your first 3% contributed
• Equity — Every full-time employee shares in our success

🛂 Visa & Eligibility

Visa sponsorship information not specified.