As a Senior Software Engineer - ML, you will design and implement ML systems for legal data processing, fine-tune LLMs, and collaborate with teams to deliver impactful AI features.
About Us
E-Verify Participation Notice
Equal Employment Opportunity (EEO) Statement
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.
About the Role
We’re hiring a Senior Software Engineer - ML to join our Applied AI team at Supio. You’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.
What You’ll Do
- 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 Supio’s ML roadmap.
What We’re Looking For
- Strong coding skills: You build production systems, not just research prototypes. Python expertise is required; experience with TypeScript 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.
Nice to Have
- 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 of-page PDFs, mixed media, etc.).
- Grit, adaptability, and curiosity—competitive gamers or analytical thinkers who enjoy complex strategy problems tend to thrive here.
What You’ll Work On in the First 6 Months
- Building ML pipelines for classification, clustering, and semantic matching.
- Deploying and monitoring fine-tuned LLMs for document summarization and case analysis.
- Implementing Supio’s homegrown RAG framework across major client streams.
- Delivering measurable impact by increasing model reliability and reducing processing time.
How Leveling Works
We intentionally hire this role across multiple levels. During the interview process, we assess technical depth, ownership, system thinking, and impact. Final leveling and compensation are determined based on demonstrated ability and experience.
Compensation
As an early-stage startup, we offer a competitive compensation package that includes base salary, meaningful equity, and benefits. Equity grants are designed to ensure employees share in the long-term success and upside of the company.
Base Salary: $190,000 - $255,000 annually
Actual compensation may vary outside of these ranges based on a number of factors, including a candidate’s qualifications, skills, competencies, experience, and geographic location.
Compensation & Benefits
- 💰 Competitive Salary + Meaningful Equity
- 💹 401(k)
- ⚕️ Health, Dental, Vision, and Life Insurance
- 🏝 Flexible Time Off + Holidays
- 🧑💻 High-autonomy work environment, every Tuesday is a Remote Work Day
- 🥗 DoorDash subsidies for breakfast and dinner; Daily lunch options
- 🧋 Boba Wednesdays
- 🚃 Monthly commuter subsidies and pre-tax parking contribution
- 🚀 Team gatherings and offsites
Supio participates in E-Verify, an employment authorization program through the U.S. Department of Homeland Security and the Social Security Administration.
Supio is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Top Skills
AWS
Azure
GCP
Go
Llm
Ml
Python
Rag
Typescript
Similar Jobs
Security • Software • Cybersecurity
As an AI Engineer, you will develop AI security capabilities, integrate features for vulnerability detection, and maintain APIs for secure interactions while collaborating across teams.
Top Skills:
AIAutogenAws BedrockAzure MlGcp Vertex AiGenerative AiGraphQLHuggingface TransformersLangchainLlmsPyTorchReactReactRuby On RailsSemantic KernelTensorFlow
Security • Software • Cybersecurity
As a Staff Software Engineer in Applied AI, you will architect AI systems for vulnerability detection, collaborate across teams, and improve AI model performance.
Top Skills:
Agentic AiAIAws BedrockAzure MlCloud-Based Ai ServicesDockerGcp Vertex AiGraphQLKubernetesMlopsPyTorchReactRuby On RailsTensorFlowTransformers
Security • Software • Cybersecurity
As a Senior Software Engineer for Applied AI, you'll develop AI security capabilities, integrate AI models, and improve security workflows within HackerOne's platform while collaborating across teams.
Top Skills:
AIAWSAzure MlGCPHuggingface TransformersMlPyTorchTensorFlow
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
