Staff Machine Learning Engineer, EvenUp

• A true builder’s mentality: ready to launch, scale, and shape a new technical domain within a rapidly growing company
• Deep domain expertise in machine learning, NLP, LLMs, and generative AI, with hands-on experience taking complex systems to production
• Strong record of mentorship, with a passion for guiding team members and representing the ML team in cross-org architectural reviews
• Experience and comfort with modern ML engineering languages and frameworks—Python, PyTorch, and vector databases (e.g., Pinecone, Milvus, or FAISS)
• Excellent communication skills, with the ability to bridge the gap between applied ML research and production engineering

Desirable

• Join EvenUp as a Staff Machine Learning Engineer and build the future of personal injury law technology
• This is a unique opportunity to lead the design and architecture of high-visibility, high-impact generative AI products that are core to our customer experience and business growth
• You’ll tackle the most complex legal document challenges by developing and deploying models that power Piai™, our proprietary claims-intelligence platform
• You’ll partner closely with Product, Research, and Infrastructure leaders to shape our technical strategy and roadmap, owning critical areas like Retrieval-Augmented Generation (RAG), vector search, and fine-tuning frameworks
• In this high-priority role, you’ll be empowered to drive innovation, mentor a top-tier ML team, and set the vision for how machine learning will shape both our customer impact and company success
• The right leader will see their work translate to tangible product launches, a robust ML foundation, and a direct influence on the success of an ambitious, fast-growing company
• Lead the design and architecture of large-scale ML systems for 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 and evaluation frameworks
• Provide hands-on technical leadership by reviewing designs, code, and system proposals to elevate the technical bar across the ML engineering org
• Collaborate cross-functionally with Product and Engineering to translate ambiguous business goals into robust, impactful ML architectures
• Drive innovation and prototyping in semantic search and generative AI evaluation, ensuring new techniques like LoRA are effectively integrated into production
• Own the frameworks and abstractions that make ML workflows reproducible, scalable, and reusable across the company
• Establish standards for system evaluation, focusing on relevance, latency, cost efficiency, and reliability metrics
• Influence the long-term roadmap by identifying gaps in ML tooling, infrastructure, and developer experience
• Mentor and guide other engineers, fostering a culture of technical excellence and continuous growth