Role overview

Senior ML Engineer

Requirements and responsibilities

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Details

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

You can learn more about us here:

  • https://www.chess.com/article/view/how-chess-com-virtual-team-works-together
  • https://www.chess.com/about
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