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. EvenUp is backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures, SignalFire, and Lightspeed. Senior Machine Learning Engineer 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're looking for a Senior Machine Learning Engineer to help build the models and systems powering Piai™, our proprietary claims-intelligence platform. You'll work across the ML stack—from data pipelines to production model deployment—alongside ML engineers, data scientists, and legal subject‑matter experts to turn raw legal and medical data into systems that directly improve outcomes for personal‑injury clients. Design, build, and own production ML systems across the full lifecycle—problem framing, data strategy, training, evaluation, deployment, and monitoring. Architect scalable data pipelines that handle structured, unstructured, and embeddings‑based data for training and inference. Partner with data scientists and product managers to translate ambiguous business problems into concrete ML system designs. Apply and productionize state‑of‑the‑art techniques across NLP, information retrieval, and generative AI where the problem calls for it. Define and implement evaluation strategies—quality metrics, human‑in‑the‑loop review,



automated benchmarks—to ensure model reliability. Drive scalability and efficiency across ML workflows, from large‑scale data processing to real‑time inference. Work with ML platform engineers to integrate models and frameworks into production environments. Mentor other engineers and contribute technical judgment to hiring and calibration as the team grows. 5+ years building and deploying machine learning systems in production. Robust software engineering fundamentals—Python, distributed systems, API design. Experience owning the full ML lifecycle, not just model training in isolation. Experience mentoring other engineers and influencing technical direction beyond your own code. Ability to work hybrid (3 days your choice) in our San Francisco or Toronto Canada office. Experience with NLP, LLMs, or generative AI—embeddings, fine‑tuning (LoRA or other PEFT), or prompt engineering. Familiarity with vector databases (Pinecone, Weaviate, FAISS, Milvus, Elasticsearch/OpenSearch) or orchestration frameworks (LangChain, LlamaIndex). Experience with evaluation methodologies for generative AI—RAG benchmarks, hallucination reduction, factual grounding. Background in legal tech, healthcare, or other high‑stakes, regulated domains. Choice of medical, dental, and vision insurance plans for you and your family. 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. 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. 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.

📌 Machine Learning Engineer- Cloud Deployment (Canada)
🏢 EvenUp
📍 Canada