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Über
San Francisco (hybrid), Toronto (hybrid) Employment Type
Full time Location Type
Hybrid Department
Data Science Compensation
San Francisco — $136K – $204K • Offers Equity Toronto, Canada — CA$124K – CA$187K • 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. Overview
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 EvenUp’s career page. What we look for
We are seeking a curious, impact-driven early career Data Scientist / Machine Learning Engineer to join our AI R&D team. 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. You’ll work with senior ML engineers, data scientists, and legal subject-matter experts to turn raw legal and medical data into production-ready models that improve justice for personal-injury clients. Responsibilities
Model research & prototyping
– Explore, implement, and benchmark ML/NLP/generative-AI methods (e.g., LLM fine-tuning, retrieval-augmented generation, document understanding). Data preparation & feature engineering
– Clean, annotate, and transform structured and unstructured case data; build reusable datasets and data loaders. Experimentation workflow
– Design experiments, run A/B tests, analyze results, and communicate findings to the wider product and engineering teams. Productionization
– Help integrate models into our microservices architecture; collaborate with MLOps engineers on packaging, testing, monitoring, and scaling. Cross-functional collaboration
– Pair with product managers, legal analysts, and software engineers to translate pain points into ML solutions and measurable product improvements. Continuous learning
– Stay current with research in LLMs, representation learning, and prompt engineering; share insights through internal talks and docs. Qualifications
Education:
Ph.D., M.S. or B.S. in Computer Science, Machine Learning, Data Science, Statistics, Computational Linguistics, or a closely related field Core expertise: Solid grounding in machine-learning fundamentals (supervised & unsupervised learning, evaluation metrics, overfitting/regularization). Hands-on experience with NLP or generative-AI techniques (e.g., transformers, embeddings, sequence-to-sequence models, LLMs). Technical stack: Proficiency in Python and ML/NLP libraries such as PyTorch, TensorFlow, Hugging Face, spaCy, or similar. Familiarity with SQL and data-engineering concepts (ETL, versioned datasets, notebooks). Nice-to-have: exposure to cloud platforms (AWS/GCP), experiment-tracking tools (Weights & Biases, MLflow), or containerized deployment (Docker/Kubernetes). Mindset & people skills: Eagerness to learn from senior teammates and iterate quickly in a fast-moving startup. Clear, concise communication—both written and verbal. Strong analytical thinking and a bias toward shipping pragmatic, high-impact solutions. Location
Hybrid – We have offices in San Francisco and Toronto Notice to Candidates
EvenUp has been made aware of fraudulent job postings and unaffiliated third parties posing as our recruiting team. We have no affiliation with these situations. We post open roles on our career page or reputable job boards, and all official recruitment emails will come from trusted domains. Do not submit resumes via email or social media unless through our careers page. If you receive a message from someone impersonating EvenUp, please report it to talent-ops-team@evenuplaw.com. Benefits & Perks
We offer a total rewards package including: Medical, dental, and vision insurance plans for you and your family Life, accident, or critical illness insurance options Flexible paid time off, sick leave, short-term and long-term disability Holidays: 10 US observed and Canadian provincial holidays Home office stipend 401(k) for US-based employees and RRSP for Canada-based employees Paid parental leave Local in-person meet-up program Hubs in San Francisco and Toronto Compensation Range: $136K - $204K
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Sprachkenntnisse
- English
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