Senior Machine Learning Engineering Manager

EvenUp is on a mission to close the justice gap using technology and AI. We empower personal injury lawyers and victims to get the justice they deserve. Our products enable law firms to secure faster settlements, higher payouts, and better outcomes for victims injured through no fault of their own in vehicle collisions, accidents, natural disasters, and more.

We are one of the fastest-growing vertical SaaS companies in history, and we are just getting started. EvenUp is backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures, SignalFire, and Lightspeed. We are looking to expand our team with talented, driven, and collaborative individuals who seek to have a lasting impact. Learn more at www.evenuplaw.com.

Join EvenUp as our Senior Machine Learning Engineering Manager and build the future of personal injury law technology. This is a unique opportunity to create and lead a brand-new Machine Learning and Generative AI function, focusing on high-visibility, high-impact generative AI products that are core to our customer experience and business growth. You'll partner closely with Product and Engineering leaders to shape our strategy and technology roadmap, own the most critical GenAI-driven product areas including Document Generation, Knowledge Bases, Agentic Systems, and drive real product outcomes from the ground up.

In this high-priority, business-critical role, you won’t just lead—you’ll be empowered to hire, create, and scale a top-tier ML team, deliver rapid product wins early, and set a vision for how ML will shape both our customer impact and company success. The right leader will see their work translate to tangible product launches, a strong ML foundation, and a direct influence on the success of an ambitious, fast-growing company.

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  Build and lead a new Machine Learning team; drive hiring, mentoring, vision, and culture from day one.

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  Design and execute a clear roadmap across Document Generation (primary), Voice Agents, and agent-based Knowledge Base systems.

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  Provide hands-on technical leadership in LLMs, ML, and GenAI, setting best practices and engineering standards for the function.

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  Collaborate cross-functionally with Product and Engineering to align priorities, unblock teams, and ensure delivery of impactful solutions.

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  Deliver visible product impact fast, with clear successes in the first 90 days—especially within Document Generation—and scale the team to a robust, autonomous ML function within the first year.

• Proven success building and managing high-performing ML or Data Science teams, ideally from scratch in fast-paced, startup-like environments.

• Deep domain expertise in machine learning, NLP, LLMs, and generative AI, with hands-on experience taking systems to production.

• Excellent cross-functional communication and leadership skills, with a strong record of partnering closely with Product and Engineering.

• Experience and comfort with ML engineering languages and frameworks—Python, PyTorch (or similar), and modern LLM/generative AI tooling.

• A true builder’s mentality: ready to launch, scale, and shape a new technical domain within a rapidly growing company.

• Experience in industries such as SaaS, fintech, big tech, or startups, with roles such as Senior Engineering Manager (ML), Director/Head of ML, or Senior Applied Scientist Manager.

• 3+ years of experience directly leading and managing a machine learning or data science team, and at least 5+ years of hands-on professional experience in machine learning engineering or related fields.

• Deep hands-on expertise in machine learning, NLP, LLMs, and generative AI, with a successful record of deploying production ML systems.

• Strong experience with Python and major ML/NLP frameworks (such as PyTorch, TensorFlow, Hugging Face, or similar).

• Demonstrated ability to build teams and functions from scratch, lead roadmap development, and drive execution in fast-paced, ambiguous environments.

• Experience working in a high-growth startup environment.

• Excellent cross-functional communication and leadership skills, with a track record of partnering closely with Product and Engineering stakeholders.

• PhD in Machine Learning, Computer Science, or other quantitative fields.

• Passion for EvenUp's mission of driving fairness and accessibility in the legal domain.

• Ability to work in a hybrid setting from one of our office hubs in Toronto or San Francisco.

EvenUp has been made aware of fraudulent job postings and unaffiliated third parties posing as our recruiting team – please know that we have no affiliation or connection to these situations. We only post open roles on our career page (evenuplaw.com/careers) or reputable job boards like our official LinkedIn or Indeed pages, and all official EvenUp recruitment emails will come from the domains @evenuplaw.com, @evenup.ai, @ext-evenuplaw.com, no-reply@ashbyhq.com or no‑reply@canditech.io email addresses.

To ensure fairness and proper consideration, we do not accept resumes or expressions of interest via email or social media messages. If you’re interested in a role, please submit your application directly through our careers page.

If you receive communication from someone you believe is impersonating EvenUp, please report it to us at talent-ops-team@evenuplaw.com. Examples of fraudulent domains include “careers-evenuplaw.com” and “careers-evenuplaws.com”.