Senior Machine Learning Engineer, EvenUp
Systems
$176-265k
Toronto pay range: CA$147K – CA$220K. Plus equity
AI-driven support for personal injury lawyers
Be an early applicant
AI-driven support for personal injury lawyers
201-500 employees
Be an early applicant
$176-265k
Toronto pay range: CA$147K – CA$220K. Plus equity
201-500 employees
Company mission
To close the justice gap using technology and AI.
Role
Who you are
- Experience with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus, Elasticsearch/OpenSearch)
- Familiarity with retrieval frameworks (LangChain, LlamaIndex, custom retrieval pipelines)
- Strong software engineering skills (Python, distributed computing, APIs)
- Strong knowledge of transformer models (LLMs, embeddings, fine-tuning methods like LoRA, PEFT)
- Understanding of evaluation methodologies for generative AI (RAG benchmarks, hallucination reduction, factual grounding)
What the job involves
- We are looking for a curious, impact-driven early career Machine Learning Engineer eager to join EvenUp's mission
- You’ll develop and deploy models that power Piai™, our proprietary claims-intelligence platform, with a focus on machine learning, natural-language processing, and generative AI
- Working alongside senior ML engineers, data scientists, and legal subject-matter experts, you’ll turn raw legal and medical data into production-ready models that directly improve justice for personal-injury clients
- Design and implement end-to-end ML systems for retrieval-augmented generation (RAG), vector search, and fine-tuning pipelines
- Build and optimize data pipelines that integrate structured, unstructured, and embeddings-based data into ML workflows
- Develop frameworks and reusable components for data extraction, evaluation, and benchmarking of LLMs and other models
- Collaborate with data scientists and product teams to translate business problems into ML system designs
- Research, prototype, and productionize state-of-the-art techniques in semantic search, embeddings, and prompt engineering
- Implement evaluation strategies for ML systems, including relevance metrics, quality scores, and human-in-the-loop workflows
- Ensure scalability and efficiency of ML workflows, including large-scale embedding generation and retrieval pipelines
- Work with machine learning platform engineers to integrate ML frameworks into production environments
- Document system architectures and create internal best practices for building ML/AI frameworks
Our take
Every year, millions of personal injury cases in the US are resolved with only a small fraction going to trial, leaving many victims potentially under-compensated due to inaccurate settlement proposals. EvenUp aims to change this by leveraging AI technology to streamline the assessment of injury cases.
The AI tools evaluate raw case files, including medical and police records, creating tailored "demand packages" that present comprehensive compensation arguments. This improves lawyer performance and victim outcomes.
Despite concerns about AI bias and privacy, EvenUp has garnered significant investor interest, closing a funding round in 2024 that was one of the largest in the history of legal AI. Now valued at over $1 billion, it is investing in its team and introducing new techniques and products for personal injury and other legal areas.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 3 rounds)
Oct 2024
$135m
SERIES D
Sep 2024
$35m
SERIES C
Total funding: $220m
Company benefits
- Flexible working hours to match your style
- Offsites - get to meet your coworkers on a fully-expenses trip ever 6-12 months
- A variety of virtual team events such as game nights & happy hours
- Choice of medical, dental, and vision insurance plans for you and your family
- Flexible paid time off and 10+ holidays per year
- A stipend to upgrade your home office for fully-remote roles
- 401k for US-based employees 🇺🇸
Company HQ
The Castro, San Francisco, CA
Leadership
Rami Karabibar
(Co-founder & CEO)Graduated from the McGill University with a Bachelor's Degree in Investment Management. Previously worked as a Management Consultant at Bain & Company and as a Startup Generalist at Zoomer.
Raymond Mieszaniec
(Co-founder & COO)Previously co-founded EquitySim. Also worked as a Risk Consultant at PwC Hong Kong and Mainland China and as an Accountant at Scotiabank.
Saam Mashhad
(Chief of Product & Legal Operations)Previously worked as a Law Clerk at the Superior Court of Quebec. Also co-founded Compass Startup & Legal Clinic where they served as the Director for 3 years before becoming an Associate at Norton Rose Fulbright.
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