Senior Machine Learning Engineer - LLMs & Document AI at EvenUp

San Francisco, California, United States

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$176,000 – $265,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Legal Technology, Artificial IntelligenceIndustries

Requirements

Candidates should possess 5+ years of experience in machine learning with multiple models deployed in operational settings and hold an MS or PhD in Machine Learning, Computer Science, or another quantitative field. Strong proficiency with the latest Large Language Model (LLM) technologies, expertise in areas like deep learning, reinforcement learning, probabilistic modeling, or optimization, and high proficiency in a procedural programming language such as Python are required. Excellent communication and collaboration skills, along with the ability to translate cutting-edge research into practical solutions, are also essential.

Responsibilities

The Senior Machine Learning Engineer will design and refine ML models for entity/relationship extraction, document structure understanding, and information retrieval from legal and medical text. Responsibilities include conducting hands-on data analysis to ensure high-quality training and evaluation datasets, tackling long-context and multi-document reasoning challenges, and developing strategies to reduce hallucinations and improve factual consistency. The role also involves leading LLM fine-tuning using reinforcement learning and parameter-efficient fine-tuning techniques, experimenting with advanced prompt engineering, and contributing to a rigorous modeling culture through peer code reviews and knowledge sharing. Collaboration with product, engineering, and legal experts to deliver business-impactful solutions is also a key part of the role.

Skills

Machine Learning

Document AI

Entity Extraction

Relationship Extraction

Information Retrieval

Reasoning

Data Analysis

EvenUp

Legal services for personal injury cases

About EvenUp

EvenUp Law provides legal services focused on personal injury, trucking accidents, and medical malpractice. The firm operates in multiple states, including Texas, Pennsylvania, California, Indiana, and Georgia. Its business model is based on a contingency fee structure, meaning they only receive payment if they win a case, taking a percentage of the settlement or judgment. What sets EvenUp Law apart from its competitors is its detailed case preparation and the ability to analyze cases like an adjuster or defense attorney, which leads to higher settlement amounts and quicker resolutions for clients. The firm also maintains a database of similar injuries and their values, which helps in providing accurate damage estimates. The goal of EvenUp Law is to save clients time and stress while ensuring they receive fair compensation for their injuries.

San Francisco, CaliforniaHeadquarters

2019Year Founded

$214MTotal Funding

SERIES_DCompany Stage

LegalIndustries

201-500Employees

Risks

Increased competition from other legal tech startups could erode EvenUp's market share.

Reliance on a contingency fee model poses financial risks with unsuccessful cases.

Potential regulatory changes in AI use could impact EvenUp's operations.

Differentiation

EvenUp uses AI to automate legal document creation, reducing time and costs.

The company targets the $20 million insurance claim market with AI-driven solutions.

EvenUp's meticulous case preparation results in high settlement amounts and quick resolutions.

Upsides

Recent $135 million Series D funding shows strong investor confidence in EvenUp.

Launch of AI assistant Litty highlights growth in generative AI for legal automation.

Strategic board appointments could open new avenues for growth and partnerships.

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