Staff Machine Learning Engineer (Systems)
EvenUp
Location
San Francisco (hybrid), Toronto (hybrid)
Employment Type
Full time
Location Type
Hybrid
Department
Data Science
Compensation
- San Francisco$215K – $323K • Offers Equity
- Toronto, CanadaCA$180K – CA$271K • Offers Equity
The salary range provided reflects the compensation that EvenUp reasonably expects to offer for this role. The specific salary within this range will be determined based on various factors, including the candidate's relevant experience, education, skills, location, and alignment with the role's responsibilities.
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.
At EvenUp, we leverage cutting-edge AI to bring fairness and accessibility to the legal system. Tackling the most complex legal document challenges requires expertise in data quality, robust model development, and ongoing innovation.
We are looking for an experienced Staff Machine Learning Engineer eager to join EvenUp's mission. You’ll develop and deploy models that power Piai™, our proprietary claims-intelligence platform, with a focus on machine learning, natural-language processing, and generative AI. Working alongside senior ML engineers, data scientists, and legal subject-matter experts, you’ll turn raw legal and medical data into production-ready models that directly improve justice for personal-injury clients.
Core Responsibilities
Lead the design and architecture of large-scale ML systems for retrieval-augmented generation (RAG), vector search, and fine-tuning frameworks across multiple product lines.
Define and drive technical strategy and best practices for ML system design, including embedding pipelines, evaluation frameworks, and integration with vector databases.
Mentor and guide other engineers by reviewing designs, code, and system proposals to elevate the technical bar across the ML engineering org.
Partner with product, research, and infra teams to translate ambiguous business and research goals into robust ML system architectures.
Drive innovation and prototyping in areas such as semantic search, generative AI evaluation, and fine-tuning techniques, with a focus on production-readiness.
Own the frameworks and abstractions that make ML workflows reproducible, scalable, and reusable across the company.
Establish standards for system evaluation, including relevance, latency, cost efficiency, and reliability metrics, and ensure they are consistently applied.
Act as a bridge between applied ML research and engineering, ensuring that new techniques (LoRA, retrieval optimizations, etc.) are integrated into production frameworks effectively.
Influence long-term roadmap and platform direction by identifying gaps in ML tooling, infrastructure, and developer experience.
Represent the ML engineering team in cross-org architectural reviews, ensuring alignment with platform, data, and infra strategies.
Optional Skills
Experience with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus, Elasticsearch/OpenSearch).
Familiarity with retrieval frameworks (LangChain, LlamaIndex, custom retrieval pipelines).
Strong software engineering skills (Python, distributed computing, APIs).
Strong knowledge of transformer models (LLMs, embeddings, fine-tuning methods like LoRA, PEFT).
Understanding of evaluation methodologies for generative AI (RAG benchmarks, hallucination reduction, factual grounding).
Notice to Candidates:
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”.
Benefits & Perks:
As part of our total rewards package, we offer attractive benefits and perks to our employees, including:
Choice of medical, dental, and vision insurance plans for you and your family
Additional insurance coverage options for life, accident, or critical illness
Flexible paid time off, sick leave, short-term and long-term disability
10 US observed holidays, and Canadian statutory holidays by province
A home office stipend
401(k) for US-based employees and RRSP for Canada-based employees
Paid parental leave
A local in-person meet-up program
Hubs in San Francisco and Toronto
Please note the above benefits & perks are for full-time employees
EvenUp is an equal opportunity employer. We are committed to diversity and inclusion in our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Compensation Range: $215K - $323K