Senior ML Engineer

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🕒 March 7

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Chess.com

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2007

🎮 Gaming

📚 Education

📱 Media

💰 Private Equity Round on 2022-01

Gaming • Education • Media

Chess. com is the leading online platform for playing and learning chess, offering a wide range of features such as live gameplay with other players, customizable training bots, chess puzzles, and comprehensive lessons. The platform is highly regarded for enhancing players' pattern recognition and overall chess skills. Chess. com also provides coverage of major chess events like the FIDE World Championship. With a focus on creating a supportive and engaging community for chess players of all levels, Chess. com is a go-to resource for anyone interested in improving their chess game or enjoying competitive play.

📋 Description

• 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!)