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UpstartUpstartUnited States

Senior Applied ML Engineer

Senior Applied ML Engineer building and shipping user-facing LLM and generative AI features. Own architecture for production ML systems, partner cross-functionally with product/research teams, and establish best practices for prompt engineering and model evaluation. Requires 4+ years software engineering with 2+ years on ML products, strong backend skills.

159k – 232k/yr
Remote4+ YOEML Engineering

About the role

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

Minimum qualifications

  • 4+ 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

Skills

PythonFastAPIFlaskKubernetesDockerTerraformLLMsLangChainllamaindexOpenAIRAGfaisspineconeReact

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