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Role Description

You believe in the power of ML and AI to build amazing, interesting, and insightful products and services for humanity… and you’d love to do that in chess!

• Own ML-driven product features, identifying opportunities through to modeling, deployment, experimentation, and impact.
• Partner with Product, Leadership, Growth, and Data Science to determine which problems should (and shouldn’t) be solved with ML, define success metrics, and iterate based on real-world performance.
• Design, build, and ship scalable ML systems, including data pipelines, training workflows, and production model serving infrastructure.
• Prototype rapidly and iterate regularly, developing repeatable evaluation frameworks, running experiments, and improving models based on results.
• Shape our ML architecture and MLOps practices, establishing standards for experimentation, deployment, monitoring, and retraining as we scale.
• Drive innovation in Generative AI, exploring how we can best use LLMs and agents to power new user experiences and internal productivity tools.
• Provide technical leadership and mentorship, mentoring more junior team members, influencing our roadmap, and raising AI/ML literacy across the company.

Qualifications

• 5+ years of demonstrated, hands-on experience building scaled ML systems, training large ML models, or equivalent experience.
• 1+ year of AI engineering experience.
• Strong technical skills and judgment around coding, testing, and building for scale.
• Strong practical ML knowledge, solid knowledge of ML theory, and a working understanding of the AI application stack and lifecycle in the context of foundation models, from evaluation to deployment.
• High sense of ownership and a drive to deliver impact in a fast-paced, evolving, ambiguous environment.

Benefits

• This is a full-time opportunity.
• We are 100% remote (work from anywhere!).