Join a hands-on engineering role where you will design, ship and run reliable software and machine learning services while working closely with customers to solve real problems.In this role, you will:

• Design, build, test, deploy and operate software and machine learning services across their full lifecycle, from discovery and systems design to production monitoring and iteration.
• Translate customer goals and pain points into secure, maintainable and production-quality solutions that meet service expectations and solve the underlying problem.
• Own quality end to end through testing strategy, observability, incident response, documentation and continuous improvement of code, models and architecture.
• Contribute to engineering excellence through code reviews, design feedback, RFCs and by building extensible systems that enable other teams to move faster.
• Develop and productionize models with strong discipline around data pipelines, training and inference workflows, versioning, reproducibility and model performance monitoring.

You will thrive if:

• You are a full-stack engineer with strong depth in machine learning, modeling and data systems, and you are comfortable owning services in production.
• You have experience designing distributed systems and ML platforms with reliability, scalability, security and failure handling built in from the start.
• You apply the right testing and quality strategy for the level of system risk, and you care deeply about observability, operational ownership and safe delivery practices.
• You communicate technical decisions clearly to both technical and non-technical audiences, and you write thoughtful design docs and RFCs.
• You work with high autonomy, use AI-assisted development tools effectively and critically review generated code rather than accepting it at face value.