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Staff Machine Learning Engineer

EvenUp8 days ago
San Francisco Bay Area, Toronto
$215,000 - $323,000/yearly
Staff

Top Benefits

Flexible working hours
Medical, dental, vision insurance
Flexible paid time off + 10+ holidays

About the role

Who you are

  • We are looking for an experienced Staff Machine Learning Engineer eager to join EvenUp's mission
  • 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

  • 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
  • Lead the design and architecture of large-scale ML systems for retrieval-augmented generation (RAG), vector search, and fine-tuning frameworks across multiple product lines
  • Define and drive technical strategy and best practices for ML system design, including embedding pipelines, evaluation frameworks, and integration with vector databases
  • Mentor and guide other engineers by reviewing designs, code, and system proposals to elevate the technical bar across the ML engineering org
  • Partner with product, research, and infra teams to translate ambiguous business and research goals into robust ML system architectures
  • Drive innovation and prototyping in areas such as semantic search, generative AI evaluation, and fine-tuning techniques, with a focus on production-readiness
  • Own the frameworks and abstractions that make ML workflows reproducible, scalable, and reusable across the company
  • Establish standards for system evaluation, including relevance, latency, cost efficiency, and reliability metrics, and ensure they are consistently applied
  • Act as a bridge between applied ML research and engineering, ensuring that new techniques (LoRA, retrieval optimizations, etc.) are integrated into production frameworks effectively
  • Influence long-term roadmap and platform direction by identifying gaps in ML tooling, infrastructure, and developer experience
  • Represent the ML engineering team in cross-org architectural reviews, ensuring alignment with platform, data, and infra strategies

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

About EvenUp

Technology, Information and Internet
201-500

EvenUp's vision is to help these injury victims get the justice they deserve, irrespective of their income, demographics, or legal representation.