Founding Machine Learning Engineer

About the Role A seed-stage enterprise AI infrastructure startup is building AI-driven knowledge discovery systems from the ground up — and is looking for a Founding Machine Learning Engineer to lead this charge. This is a high-impact, early team opportunity where you'll shape both the technical foundation and the strategic direction of all ML efforts, working directly with the founding team to define the product roadmap and long-term AI vision. The company provides an enterprise context layer that makes AI agents reliable, accurate, and secure for mission-critical operations in highly regulated industries such as insurance, asset management, banking, healthcare, and logistics. The platform automatically builds a holistic domain model across enterprise data sources — mapping relationships, resolving conflicts, and delivering real-time governed context to AI agents at runtime. This role is on-site in San Mateo, CA . Visa sponsorship is available. What You'll Do Design and deploy production-grade models and pipelines for Knowledge Extraction, Natural Language Understanding (NLU), and Information Retrieval. Drive advances in unsupervised learning and fine-tune large language models to build scalable, high-performance AI applications. Make key architectural decisions and iterate hands-on, balancing rapid development with long-term scalability. Collaborate with the founding team to shape the product roadmap and set the strategic direction for AI initiatives. Hire and mentor the ML team as the company scales. What We're Looking For Must-haves (dealbreakers): 5+ years of experience as a Machine Learning Engineer building and deploying production ML systems, models, or data pipelines. Demonstrated experience building and fine-tuning Large Language Models (LLMs) or working with transformer-based architectures. Hands-on experience designing and deploying end-to-end ML pipelines and systems in production environments. Required skills & experience: Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or equivalent) for model development and experimentation. Experience with NLP tasks including text classification, entity extraction, or semantic understanding. Experience building information retrieval systems, search systems, or knowledge graphs. Experience with unsupervised learning techniques and methods for discovering patterns in unlabeled data. Experience working with large-scale data infrastructure, data lakes, or distributed systems for ML workloads. Track record of making architectural decisions and owning technical direction in early-stage or high-impact projects. A builder mentality — thrives in ambiguous, fast-moving environments and can move fast without sacrificing quality. Nice to have: Experience with prompt engineering, retrieval-augmented generation (RAG), or other generative AI techniques. Background in data discovery, data cataloging, or enterprise data management systems. Prior experience at early-stage startups or founding teams building ML products from scratch. Experience with ML model evaluation, monitoring, and optimization in production systems. Location & Logistics Location: On-site in San Mateo, CA, US (full-time, in-person). Visa sponsorship: Available. Employment type: Full-time.