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Chess.comChess.comUnited States

Senior ML Engineer

Senior ML Engineer owns ML-driven product features end-to-end, from ideation to deployment and impact measurement. Partners cross-functionally to build scalable ML systems, drive Generative AI innovation, and mentor juniors. Requires 5+ years ML experience and strong AI engineering skills.

Salary not listed
Remote5+ YOEML Engineering

About the role

What you'll do

  • 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.

Preferred Skills

  • 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.

Skills

Machine LearningMLOpsGenerative AILLMsAI AgentsData PipelinesModel TrainingModel DeploymentPythonExperimentation Frameworks

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