Machine Learning Engineer

Overview Crossing Hurdles is a recruitment firm that assists our clients to hire best talent. About the Company: It is a Cognitive AI platform that automates low-level cognitive tasks involving clinical data and knowledge - tasks that underlie patient care, revenue cycle, clinical research, and population health. Location Remote-first (U.S. only), core hours in Pacific time. Bay Area team meets in our San Francisco office weekly; relocation encouraged. About Role We’re looking for a Senior Data/AI/ML Engineer (7+ years) with expertise in data-intensive systems, strong software engineering skills, and hands-on experience in AI/ML/NLP to help build and scale our clinical data intelligence platform. What you/'ll do Build and improve clinical/health information extractors and summarizers that directly power applications used by clinicians daily. Scrape, collect, extract, transform, query, analyze, mine, and distill structured/unstructured data to evaluate system quality and performance, draw insights, and expand/refine our clinical knowledge graph. Build and improve supporting data/AI/ML systems and automations. Develop and deploy secure code, maintaining confidentiality, integrity, and availability of information systems and processes in compliance with HIPAA and SOC 2. Participate in rotating on-call duties to ensure system uptime. Must-Have Qualifications Strong expertise in Python and SQL, with proven ability to work with large and messy datasets. Hands-on experience in Machine Learning / NLP, particularly with classifiers, summarization, knowledge graphs, or LLMs (GenAI/LLM Ops experience is a plus). A solid track record of building production-ready, data-intensive systems (beyond research or prototypes). Previous startup or early-stage experience, with the ability to thrive in a fast-paced, remote-first, and evolving environment. Full-stack capability – primarily backend-focused, but comfortable making quick changes in React/TypeScript when needed. High adaptability, able to handle open-ended problems, shifting priorities, and ship iteratively. Strong software engineering fundamentals, with a balance of quick problem-solving and building robust, scalable solutions. Nice-to-Have Qualifications Background in healthcare or clinical data. An advanced degree (MSc/PhD) in CS, Engineering, or another STEM discipline from a top university. Prior experience collaborating directly with clinicians or domain experts. Why candidates should join Make an impact: Help clinicians save hours per patient by turning raw health data into actionable insights. Work on cutting-edge AI: Apply LLMs, knowledge graphs, and advanced NLP to real-world healthcare problems. Grow with us: Join a fast-moving Series A startup (~20 people) where your work ships quickly and shapes the product. #J-18808-Ljbffr

Created: 2025-09-24