Machine Learning Engineer, EvenUp

• B.S., M.S., or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, Computational Linguistics, or a related field
• Solid grounding in ML fundamentals - supervised and unsupervised learning, evaluation metrics, overfitting and regularization
• Hands-on experience with NLP or generative AI techniques - transformers, embeddings, sequence-to-sequence models, or LLMs
• Proficiency in Python and ML/NLP libraries such as PyTorch, TensorFlow, Hugging Face, or spaCy
• Familiarity with SQL and basic data engineering concepts - ETL, versioned datasets, notebooks
• Strong analytical thinking, clear communication, and eagerness to learn and iterate quickly in a fast-moving startup
• Ability to work hybrid (3 days your choice) in our San Francisco or Toronto, Canada office

Desirable

• We're looking for a Machine Learning Engineer to join our ML team at EvenUp. 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 outcomes for personal-injury clients
• Explore, implement, and benchmark ML, NLP, and generative AI methods - including LLM fine-tuning, retrieval-augmented generation, and document understanding
• Clean, annotate, and transform structured and unstructured case data, and build reusable datasets and data loaders
• Design experiments, run A/B tests, analyze results, and communicate findings to product and engineering teams
• Help integrate models into our production systems, partnering with ML platform engineers on testing, monitoring, and scaling
• Pair with product managers, legal analysts, and software engineers to translate real problems into ML solutions and measurable improvements
• Stay current with research in LLMs, representation learning, and prompt engineering, and share what you learn with the team