Plenful - Staff Machine Learning Engineer
Requirements
• 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. • 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. • What your first 90 days look like • By day 30, you have reviewed our agents, evals and training pipeline and written down the three biggest gaps. By day 90, you have shipped a post-training or evaluation improvement that moved a production metric, and published the plan the team follows for the next two quarters.
Responsibilities
• You set the direction for how our agents are built • Define the architecture for production agents: tool use, retrieval, state and context management, routing, orchestration, tracing and failure recovery. • Turn what works into patterns other engineers reuse. • Make the calls on build versus buy for models and platform pieces. • You own our post-training strategy • Decide where supervised fine-tuning, preference optimization, distillation and reinforcement learning pay off, and where they do not. • Train and ship LLMs and vision-language models for healthcare tasks, and build the in-house capability to keep doing it. • Prove every gain with evaluation that holds up in production. • You define what good looks like • Set the AI quality strategy: automated graders, calibrated LLM judges, regression suites, human review, failure taxonomies and offline-to-online validation. • Make eval results the basis for release decisions. • You build loops that improve themselves • Design the systems that turn production failures and user feedback into better datasets, evals and models. • Set the standard for dataset versioning, observability and MLOps so every team's work is reproducible and measurable. • You raise the bar for everyone • Co-own the 12-month ML roadmap with engineering and product leaders, balancing near-term wins against longer bets. • Lead technical reviews, mentor Senior engineers, and help us hire. • Build privacy in by design: minimum necessary data, de-identified or synthetic data where it works, and HIPAA-aware practices throughout.
Benefits
• 🚀 Mission-Driven, World-Class Team — Join an exceptional group of professionals aligned around a meaningful mission and committed to making an impact • Mission-Driven, World-Class Team • 📈 Opportunities for Growth — Strengthen your expertise through collaboration with experienced, high-performing leaders across the organization • Opportunities for Growth • 🏢 Flexible Hybrid Work Environment — We're remote-first, with meaningful office presence in San Francisco and New York. R&D roles follow a hybrid model, with two days per week in our San Francisco office • Flexible Hybrid Work Environment • 🏥 Healthcare Coverage — Full medical, dental, and vision insurance for you and participation for your family • Healthcare Coverage • 💰 401(k) with Company Match — Plenful matches 50% of your first 3% contributed • 401(k) with Company Match • 📊 Equity — Every full-time employee shares in our success • Equity • 🌴 Unlimited PTO — Take the time you need, when you need it • Unlimited PTO • 🍽️ Daily Lunch Stipend — $100/week to cover your midday meals • Daily Lunch Stipend • 💪 Wellness Stipend — $100/month to support your health and well-being • Wellness Stipend • 🚇 Commuter Benefits — $100/month for SF and NYC-based employees • 👶 Parental Leave — Paid leave to support growing families • Parental Leave
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