Machine Learning Engineer

EvenUp • San Francisco, CA

2d • $130,000 - $205,000 • Hybrid

About The Position

EvenUp is seeking a Machine Learning Engineer to join its ML team and develop and deploy models for Piai™, its proprietary claims-intelligence platform. The role focuses on machine learning, natural-language processing, and generative AI, applying legal and medical data to production-ready models that improve outcomes for personal-injury clients. The engineer will work alongside senior ML engineers, data scientists, and legal subject-matter experts.

Requirements

• 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, including supervised and unsupervised learning, evaluation metrics, overfitting, and regularization.
• Hands-on experience with NLP or generative-AI techniques such as 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 such as ETL, versioned datasets, and notebooks.
• Strong analytical thinking, clear communication, and eagerness to learn and iterate quickly in a fast-moving startup.
• Ability to work hybrid, three days of the employee's choice, in the San Francisco or Toronto office.

Nice To Haves

• Exposure to cloud platforms such as AWS or GCP.
• Experience with experiment-tracking tools such as Weights & Biases, Gemini Enterprise Agent Platform, or MLflow.
• Familiarity with containerized deployment using Docker or Kubernetes.
• Experience in a high-growth startup environment.

Responsibilities

• Explore, implement, and benchmark machine-learning, 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 production systems, partnering with ML platform engineers on testing, monitoring, and scaling.
• Partner 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 findings with the team.

Benefits

• Choice of medical, dental, and vision insurance plans for the employee and their family.
• Additional insurance coverage options for life, accident, or critical illness.
• Flexible paid time off and sick leave.
• Short-term and long-term disability.
• 10 US observed holidays and Canadian statutory holidays by province.
• Home office stipend.
• 401(k) for US-based employees and RRSP for Canada-based employees.
• Paid parental leave.
• Local in-person meet-up program.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level