Staff Applied Machine Learning Engineer, LLM Applications

The Team Upstart's new Applied LLM team is building foundational infrastructure that democratizes access to generative AI for every product and engineering team across the company. This is a cross-functional team at the intersection of machine learning, product, and engineering. Our mission is to bring the power of ML - particularly large language models (LLMs) and generative AI - to life in Upstart's core products. As a Staff Applied Machine Learning Engineer focused on building LLM applications, you'll work closely with researchers, product managers, platform engineers, and designers to ship intelligent features that elevate the user experience and expand the capabilities of our systems. Position Location - This role is available in the following locations: San Mateo, Columbus, Austin, Remote Time Zone Requirements - This team operates on the East/West Coast time zones. Travel Requirements - This team has regular on-site collaboration sessions. These occur 3-4 days per Quarter at one of our offices. If you need to travel to make these meetups, Upstart will cover all travel related expenses. How you'll make an impact: • Design and build user-facing ML features that harness LLMs and generative AI to unlock new product capabilities • Partner with product, design, and ML research to prototype and deliver high-impact, ML-powered experiences • Own the technical architecture and implementation strategy for applied ML systems - balancing latency, observability, and iteration speed • Build scalable services and APIs that bring model outputs to users in trustworthy and intuitive ways • Collaborate across platform, infra, and legal/compliance teams to ensure ML deployments meet standards for safety, fairness, and performance • Establish and evangelize best practices for prompt design, model evaluation, and experimentation across the org What we're looking for: • Minimum qualifications: • 6+ years of software engineering experience, with 2+ years working directly on ML-driven products or intelligent systems • Proven ability to lead complex initiatives across engineering, product, and research stakeholders • Strong backend development skills (e.g., Python with FastAPI or Flask), plus experience with cloud-native tooling (e.g., Kubernetes, Docker, Terraform) • Experience integrating LLMs or ML models into production systems, including APIs and user-facing applications • Excellent communication skills and a collaborative, product-minded approach • Ability to think rigorously about system design, latency tradeoffs, and user impact when working with ML features • Preferred qualifications: • Experience shipping GenAI or LLM-powered features using frameworks like LangChain, LlamaIndex, or OpenAI APIs • Familiarity with retrieval-augmented generation (RAG), vector search (e.g., FAISS, Pinecone), and real-time inference patterns • Proficiency in full-stack development, including front-end work with React or similar frameworks • Strong intuition for prompt engineering, model testing, and evaluation methodologies • Experience navigating complex requirements around explainability, user trust, or compliance in ML applications • Track record of influencing architecture or product direction at a team or org level What you'll love: • Competitive Compensation (base + bonus & equity) • Comprehensive medical, dental, and vision coverage with Health Savings Account contributions from Upstart • 401(k) with 100% company match up to $4,500 and immediate vesting and after-tax savings • Employee Stock Purchase Plan (ESPP) • Life and disability insurance • Generous holiday, vacation, sick and safety leave • Supportive parental, family care, and military leave programs • Annual wellness, technology & ergonomic reimbursement programs • Social activities including team events and onsites, all-company updates, employee resource groups (ERGs), and other interest groups such as book clubs, fitness, investing, and volunteering • Catered lunches + snacks & drinks when working in offices #LI-REMOTE #LI-MidSenior Apply tot his job