Senior Applied AI Engineer

Senior Applied AI Engineer

Location:

Seattle
• San Francisco

Role type:
Hybrid, Full-time – Software Engineering

Supio is a trusted AI platform purpose-built for law firms, reshaping how data drives impactful outcomes. Our innovative approach blends technology with deep legal expertise, making us a leader in our field. We go beyond surface-level AI to deeply understand our customers’ daily needs, empowering law firms with unparalleled data insights. Supio delivers human-level, accurate analysis of complex data and legal records, quickly and efficiently bringing critical insights when they matter most.

Trusted by top litigation lawyers, our platform has supported over $1 billion in settlements.

Headquartered in Seattle with an office in San Francisco, we raised $60M Series B in April 2025 led by Sapphire Ventures with Mayfield and Thomson Reuters Ventures, bringing total funding to $91M. We’re scaling rapidly and looking for exceptional talent to join us in this next phase of growth.

We’re looking for passionate team members who are motivated by our mission and ready to help us achieve it.

We’re hiring a Senior Software Engineer - ML to join our Applied AI team ’ll work at the intersection of software engineering and AI—building, fine-tuning, and scaling ML systems that transform thousands of complex documents into structured, actionable data. This role is deeply hands‑on: writing production-quality code, designing scalable pipelines, and shipping features that reach 100K+ users.

If you’re a builder who thrives on solving ambiguous, data-heavy problems using ML and large language models—and you love seeing your work operating in production at scale—this is for you.

Note:

this role is an Applied AI engineer who can actually code at a senior software level, with strong applied ML/LLM experience but not research‑heavy or academic.

• Design and implement ML-powered systems that process large-scale document data (legal, medical, billing, etc.) from raw PDFs to structured insights.
• Fine‑tune LLMs and build retrieval-augmented generation (RAG) and agentic systems for real-world use cases.
• Own code from prototype to production—writing performant, maintainable Python code and integrating ML services into Supio’s core platform.
• Develop and optimize end-to-end evaluation frameworks to measure accuracy, latency, and reliability.
• Collaborate with product, design, and backend teams to bring AI features to life for real user problems.
• Work across the stack when needed: backend APIs, model serving, cloud infrastructure, and system monitoring.
• Partner directly with David Brinda (Hiring Manager) and technical leadership to shape Supo’s ML roadmap.

• Strong coding skills: you build production systems, not just research prototypes. Python expertise is required; experience with Type Script or Go is a plus.
• Hands‑on ML experience: you’ve fine‑tuned models, shipped them into production, and maintained them at scale (100K+ MAU).
• Applied AI mindset: comfortable with RAG systems, prompt engineering, agents, and data preprocessing/postprocessing for NLP tasks.
• Probabilistic thinking: you reason in uncertainty, understand performance tradeoffs, and are comfortable balancing precision and recall rather than fixed rules.
• Experience with cloud platforms (AWS, GCP, or Azure) and containerized environments for deployment.
• Clear communicator who can explain design decisions and model behavior to teammates and leaders.

• Experience in full-stack or backend engineering roles before moving into ML.
• Background in fintech, health tech, or document-heavy domains.
• Familiarity with scaling systems that process large, unstructured data (thousands-page PDFs, mixed media, etc.).
• Grit, adaptability, and curiosity—competitive gamers or analytical thinkers who enjoy complex strategy problems tend to thrive here.

• Building ML pipelines for classification, clustering, and semantic matching.
• Deploying and monitoring fine‑tuned LLMs for document summarization and case analysis.
• Implementing Supo’s homegrown RAG framework across major client streams.
• Delivering…