Early Career Machine Learning Engineer at EvenUp

San Francisco, California, United States

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$136,000 – $204,000Compensation

Entry Level & New GradExperience Level

Full TimeJob Type

UnknownVisa

Software, Artificial IntelligenceIndustries

Requirements

Candidates should possess a Ph.D., M.S., or B.S. in Computer Science, Machine Learning, Data Science, Statistics, Computational Linguistics, or a related field. A solid foundation in machine learning fundamentals, including supervised and unsupervised learning, evaluation metrics, and regularization, is essential. Hands-on experience with NLP or generative AI techniques such as transformers, embeddings, sequence-to-sequence models, or LLMs is required. Proficiency in Python and ML/NLP libraries like PyTorch, TensorFlow, Hugging Face, or spaCy is necessary, along with familiarity with SQL and basic data engineering concepts. Exposure to cloud platforms, experiment tracking tools, or containerized deployment is a plus.

Responsibilities

The Early Career Machine Learning Engineer will research, implement, and benchmark ML, NLP, and generative AI methods, focusing on LLM fine-tuning, retrieval-augmented generation, and document understanding. Responsibilities include preparing and engineering data by cleaning, annotating, and transforming case data, as well as building reusable datasets and data loaders. The role involves designing experiments, running A/B tests, analyzing results, and communicating findings. Additionally, the engineer will assist in integrating models into the microservices architecture, collaborating with MLOps engineers on deployment, and working with product managers, legal analysts, and software engineers to translate pain points into ML solutions. Continuous learning and sharing insights on LLMs and related research are also key aspects of the role.

Skills

Machine Learning

Natural Language Processing

Generative AI

Model Prototyping

Data Preparation

Feature Engineering

Experimentation

A/B Testing

Microservices Architecture

MLOps

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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