Machine Learning Engineer 1 & 2 - Systems at EvenUp · San…

Summary: EvenUp is on a mission to close the justice gap using technology and AI. They are seeking a curious, impact-driven early career Data Scientist / Machine Learning Engineer to join their AI R&D team to develop and deploy 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 Required Qualifications: - Education: Ph.D., M.S. or B.S. in Computer Science, Machine Learning, Data Science, Statistics, Computational Linguistics, or a closely related field - 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) - Proficiency in Python and ML/NLP libraries such as PyTorch, TensorFlow, Hugging Face, spaCy, or similar - Familiarity with SQL and basic data-engineering concepts (ETL, versioned datasets, notebooks) - 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 Preferred Qualifications: - Exposure to cloud platforms (AWS/GCP), experiment-tracking tools (Weights & Biases, MLflow), or containerized deployment (Docker/Kubernetes) Required Skills: Machine Learning, Natural Language Processing, Python Important Skills: Data Science, SQL, Cloud Platforms Nice-to-Have Skills: Analytical Thinking, Eagerness to Learn, Clear Communication Benefits: 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