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Why this grade This listing scored 28/100, which is an F. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Remote clarity 15 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Role specificity 3 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Freshness 0 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Pay transparency 0 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
-15 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
Engineering
About You
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!
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.
About the Opportunity
- This is a full-time opportunity
- We are 100% remote (work from anywhere!)
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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
About Us
Chess.com is one of the largest gaming sites in the world and the #1 platform for playing, learning, and enjoying chess.
We are a team of 600+ fully remote people in 60+ countries working hard to serve the global chess community. We are here to support 200M+ chess players worldwide with the best possible product, content, and tools to serve the community!
We are a tech company. A gaming company. A content company. And we do it all with passion and commitment to the game. Above all we prize our mission-driven, flat, life-celebrating, no-corporate culture, and we look forward to meeting you and learning more about what you can bring to the team.
Apply for this role Opens ats.rippling.com — the employer's own page, as linked by the source that listed this role
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Where this listing came from
- 07 Jul 2026 Company ATS employer ATS first sighting
Seen on 1 board over 41 days.