Chess.com

Senior ML Engineer

Chess.com

full-time

Posted on:

Location Type: Remote

Location: Anywhere in the World

Visit company website

Explore more

AI Apply
Apply

Job Level

About the role

  • 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.

Requirements

  • 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
  • 100% remote (work from anywhere!)
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
machine learningML systemsdata pipelinestraining workflowsmodel servingGenerative AILLMsAI engineeringcodingtesting
Soft Skills
technical leadershipmentorshipownershipimpact deliveryadaptability