Job description
EvenUp is on a mission to support injury law firms across America in providing a consistent and high standard of representation, ensuring that every injury victim who seeks legal assistance can expect a fair resolution. We’ve helped thousands of victims get fair compensation by empowering their representation with best-in-class insights, automation, and document creation.
Why we are hiring a Machine Learning Engineer:
At EvenUp, the Machine Learning Team is pivotal in leveling the playing field in legal disputes. We tackle challenging problems at the intersection of ML, information retrieval, and generative AI to create meaningful impact for plaintiffs and attorneys. As a Machine Learning Engineer, you will contribute to building scalable, innovative solutions in the domain of Document AI, working on complex legal data and leveraging cutting-edge techniques to deliver actionable insights and transformative results.
This role provides a unique opportunity to work with a proprietary dataset, solve high-impact problems, and see your contributions lead to real-world justice.
What you’ll do:
Pioneer cutting-edge Document AI systems at the forefront of generative AI innovation, building next-generation models that go beyond traditional document processing to achieve human-level understanding of complex legal and medical documents, intelligently extract key entities and relationships, perform sophisticated multi-document reasoning, and generate contextually-aware documents that transform business workflows.
Implement and advance technologies in:
Information Extraction (using traditional ML, LLMs, and multi-modal LLMs for entity recognition, relationship extraction, and document structure understanding)
Information Retrieval (query understanding, semantic search, hybrid retrieval architectures, and learning-to-rank models)
Data Management (schema design, knowledge graphs, distributed data pipelines, and petabyte-scale processing)
RAG (Retrieval-Augmented Generation) with advanced techniques like multi-hop reasoning, chain-of-thought prompting, and self-consistency checks
Prompt Engineering (few-shot learning, instruction tuning, and context window optimization)
LLM fine-tuning (parameter-efficient techniques like LoRA/QLoRA, instruction fine-tuning, and domain adaptation)
Collaborate with domain experts (legal, healthcare, etc), product managers, and engineers to translate insights into robust machine learning systems.
Create tools that empower internal teams and clients to make data-driven decisions.
Mentor junior team members, promoting a culture of excellence and collaboration.
What We Are Looking For: We recognize the breadth of skills required and do not expect candidates to have experience in all areas. We seek talent with a strong foundation in machine learning, information retrieval, or data management, with particular interest in LLM and generative AI technologies.
3+ years of experience in machine learning, data science, or similar technical role
Strong software engineering fundamentals and proficiency in Python
Demonstrated expertise in:
Classical ML techniques (regression, classification, clustering)
Deep learning frameworks (PyTorch, TensorFlow)
Natural language processing and information extraction
Large language models and prompt engineering
RAG system design and implementation
Advanced RAG techniques (multi-hop reasoning, self-consistency)
Vector databases and embedding techniques
Model evaluation and validation methods
Experience with:
LLM fine-tuning (LoRA, QLoRA, instruction tuning)
Knowledge graph construction and reasoning
Production ML system deployment
Distributed computing and data processing
Excellent communication skills with ability to:
Explain complex technical concepts clearly
Collaborate effectively with cross-functional teams
Write clear technical documentation
Sound judgment in balancing technical tradeoffs with business needs
Why Join EvenUp:
Be part of a mission-driven company making a tangible impact in the lives of injury victims.
Work at the cutting edge of Document AI, tackling challenging ML and data problems.
Collaborate with a diverse team of experts from top tech, legal, and investment firms.
Grow with a rapidly scaling company backed by world-class investors and thought leaders.
If you’re passionate about solving meaningful problems, advancing ML technologies, and making a difference, we’d love to hear from you!
Benefits & Perks:
Our goal is to empower every team member to contribute to our mission of fostering a more just world, regardless of their role, location, or level of experience. To that end, here is a preview of what we offer:
Choice of medical, dental, and vision insurance plans for you and your family
Flexible paid time off
10 US observed holidays, and Canadian statutory holidays by province
A home office stipend
401(k) for US-based employees
Paid parental leave
Sabbatical program
A meet-up program to get together in person with colleagues in your area
Offices in San Francisco and Toronto
Please note the above benefits & perks are for full-time employees
About EvenUp:
EvenUp is on a mission to level the playing field in personal injury cases. EvenUp applies machine learning and its AI model known as Piai™ to reduce manual effort and maximize case outcomes across the personal injury value chain. Combining in-house human legal expertise with proprietary AI and software to analyze records. The Claims Intelligence Platform™ provides rich business insights, AI workflow automation, and best-in-class document creation for injury law firms. EvenUp is the trusted partner of personal injury law firms. Backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures (BCV), SignalFire, NFX, DCM, and more, EvenUp’s customers range from top trial attorneys to America’s largest personal injury firms. EvenUp was founded in late 2019 and is headquartered in San Francisco. Learn more at www.evenuplaw.com.
EvenUp is an equal opportunity employer. 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.
