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, and LLMs, with a track record of solving complex modeling challenges and deploying models in operational settings
• Expertise in advanced ML techniques, including deep learning, reinforcement learning, probabilistic modeling, or optimization
• Strong record of mentorship, with a passion for guiding team members and establishing best practices for experimentation and benchmarking
• Experience and comfort with modern ML engineering languages and frameworks—specifically high proficiency in Python and major LLM technologies
• Excellent communication skills, with the ability to partner closely with both technical and non-technical stakeholders to deliver business-impactful solutions
• 5+ years of hands-on professional experience in machine learning engineering or related fields, with multiple models deployed in operational settings
• Strong proficiency with the latest LLM technologies and a demonstrated ability to apply cutting-edge research to practical solutions
• High proficiency in Python and a deep understanding of modern ML/NLP frameworks
• Demonstrated ability to lead technical strategy, mentor team members, and drive execution in fast-paced, ambiguous environments
• Experience working in a high-growth startup environment
• Excellent cross-functional leadership skills, with a track record of partnering closely with Product and Engineering stakeholders

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 development of high-visibility, high-impact generative AI models that are core to our customer experience and business growth
• You will tackle the most complex legal document challenges, turning raw legal and medical data into production-ready models that power Piai™, our proprietary claims-intelligence platform
• You’ll partner closely with Product, Research, and Engineering leaders to shape our modeling strategy, owning critical areas like Document AI, LLM fine-tuning, and sophisticated information retrieval
• 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
• Design and refine advanced Document AI models for entity/relationship extraction, document structure understanding, and sophisticated reasoning from complex legal and medical text
• Solve complex modeling challenges involving long-context and multi-document reasoning, including context segmentation and the aggregation of distributed facts
• Lead LLM fine-tuning initiatives, applying techniques like reinforcement learning with verifiable reward signals and parameter-efficient fine-tuning (e.g., LoRA, QLoRA)
• Establish rigorous evaluation standards to reduce hallucinations, improve factual consistency, and handle ambiguous or noisy data
• Drive data excellence by conducting hands-on analysis to ensure high-quality training and evaluation datasets, managing edge cases, noise, and data drift
• Experiment with and benchmark advanced prompt engineering techniques (few-shot, chain-of-thought), balancing context length with extraction accuracy
• Provide technical leadership and mentorship to a team of ML engineers and data scientists, fostering a culture of technical excellence and continuous growth
• Collaborate cross-functionally with product, engineering, and legal subject-matter experts to translate ambiguous research goals into impactful production solutions
• Act as a bridge between cutting-edge research and practical application, ensuring new techniques are integrated into our production frameworks effectively