Software Engineer, Machine Learning Infrastructure
Builds scalable ML infrastructure services for experimentation, model training, serving, and LLM applications. Requires 2+ years of software development experience plus experience with distributed systems, production ML platforms or MLOps, and high-availability operations.
About the job
Responsibilities
- Design and build scalable, reliable, and secure services for notebooks, ML model training, experimentation, serving, and LLM applications across multiple regions.
- Create services and libraries that enable ML engineers to transition seamlessly from experimentation to production across company systems.
- Work directly with product teams and ML engineers to improve day-to-day productivity.
- Own and solve technical and product challenges across diverse systems, processes, and technologies.
Requirements
- 2+ years of professional software development experience.
- Strong background in service-oriented architecture and large-scale distributed systems.
- Experience across the full software development lifecycle, including user discovery, design, implementation, testing, deployment, and operations.
- Experience working on production ML platforms, MLOps solutions, or LLM applications.
- Experience operating high-availability, low-latency systems.
- Experience partnering with other teams to drive business outcomes.
- Pragmatic approach to selecting and adjusting solutions.
Nice-to-haves
- Experience building and shipping production AI agents.
- Familiarity with LLMs and LLM frameworks.
- Experience training and shipping machine learning models to production for critical business problems.
Skills
Machine Learning, MLOps, LLMs, Llm Frameworks, AI Agents, Distributed Systems, Service-Oriented Architecture, Software Development, Model Training, Model Serving, Notebooks, Production Operations
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