Senior Machine Learning Engineer
Supio
Software Engineering
San Francisco, CA, USA
USD 155k-250k / year + Equity
Posted on Oct 27, 2025
Senior Machine Learning Engineer
San Francisco
Software Engineering
In office
Full-time
About Us
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.
Does this sound like you?
We're seeking a Senior Machine Learning Engineer to drive and scale the validation of our AI systems. You'll lead a team of applied scientists while staying hands-on, building the measurement frameworks and experimental approaches that ensure our AI systems deliver reliable results.
In this role you will:
- Design, build, and deploy ML systems that power core product features—from prototype to production.
- Work across the stack to integrate models into scalable and maintainable infrastructure.
- Conduct rigorous experimentation, data analysis, and performance evaluation to drive improvements.
- Collaborate closely with product, design, and engineering teams to align technical solutions with business goals.
- Mentor junior engineers and help establish best practices for our ML development lifecycle.
- Own projects end-to-end in a fast-paced, agile environment—wearing multiple hats when necessary.
- Stay up-to-date with research and emerging techniques to inform our ML roadmap.
Qualifications:
- Expertise in Machine Learning algorithms and LLM architectures
- Experience with developing, fine-tuning, and deploying LLMs and other advanced ML models in production environments.
- Experience with cloud-based platforms and ML infrastructure (e.g., AWS, GCP, Azure) to scale model development and deployment.
- Strong communication skills to explain complex ML and LLM concepts to non-technical stakeholders and influence decision-making at the leadership level.
Nice-to-haves:
- Experience producing and working with AI-driven or data-heavy platforms.
- Familiarity with legal technology or products in the legal industry.
- Previous experience in fast-paced startup environments or building products from the ground up.
Compensation:
Salary Range: The salary range for the SF Bay Area is $155,000-250,000 annually plus equity, with the potential for variation based on qualifications and skills.
Benefits & Perks
Supio offers an extensive benefits package and perks which include:
- Health insurance: medical, dental, and vision
- 401k
- Flexible paid time off (PTO) and company-paid holidays
- Monthly commuter subsidies
- DoorDash subsidies for breakfast and dinner
E-Verify Participation Notice
Supio participates in E-Verify, an employment authorization program through the U.S. Department of Homeland Security and the Social Security Administration.
Equal Employment Opportunity (EEO) Statement
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.
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This role requires 5 days/week in office from either SF or Seattle offices. Does that work for you? *
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Req ID: R1
