Staff Software Engineer, Machine Learning Platform

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

• 10+ years of professional software development experience, or equivalent domain expertise, with a solid background in service-oriented architecture and large-scale distributed systems.
• Track record of serving as a technical lead, with the ability to provide technical direction, lead multi-team initiatives, and mentor team members.
• Experience building and operating production ML platform in one or more areas such as model training, model serving, orchestration, or ML data systems, with requirements for performance, reliability, scalability, and cost efficiency.
• Strong product instincts and a deep understanding of the business context in which you operate.
• Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
• Demonstrated ability to work cross-functionally, collaborating effectively with ML engineers, data scientists, software engineers, product managers, and business stakeholders.
• The ability to thrive on a high level of autonomy and responsibility, and comfort operating in ambiguous environments.
• Hands-on experience using AI tools to accelerate how you work.
• Experience building large-scale ML training, serving, or data infrastructure for machine learning use cases, such as distributed training, model inference, feature stores, real-time feature computation, and model registries.
• Experience with distributed ML training systems, accelerator-backed compute, training data pipelines, experiment tracking, and model evaluation.
• Experience rapidly developing prototypes and iterating based on user feedback.
• Experience training and shipping machine learning models to production to solve critical business problems.
• Familiarity with LLMs, LLM application frameworks, and agentic AI patterns (e.g., tool use, multi-agent orchestration, retrieval-augmented generation).
• Familiarity with cloud services (e.g., AWS) and cloud-based AI and ML services (e.g., SageMaker, Bedrock, Databricks, OpenAI).
• Ability to synthesize ideas across the organization while setting a compelling technical vision.
• Comfortable working with geographically distributed teams.
• Passion for side projects, open source, or self-driven technical initiatives.