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About You
You have a passion for harnessing the power of Machine Learning (ML) and Artificial Intelligence (AI) to create insightful and innovative products and services that benefit humanity. You’re excited about the opportunity to apply these technologies in the world of chess!
Your Responsibilities
- Own ML-Driven Product Features: Identify opportunities from modeling and deployment to experimentation and measuring impact.
- Collaborate Across Teams: Work with Product, Leadership, Growth, and Data Science to prioritize challenges best suited for ML, establish success metrics, and refine solutions based on actual performance.
- Design and Build Scalable ML Systems: Develop data pipelines, training workflows, and infrastructure for deploying production models.
- Prototype and Iterate: Rapidly create prototypes and establish repeatable evaluation frameworks, running experiments to continuously enhance models based on results.
- Shape ML Architecture and MLOps Practices: Set standards for experimentation, deployment, monitoring, and retraining as our systems scale.
- Drive Innovation in Generative AI: Explore how to effectively leverage Large Language Models (LLMs) and agents to enhance user experiences and improve internal productivity tools.
- Provide Technical Leadership: Mentor junior team members, influence the company roadmap, and promote AI/ML literacy across the organization.
Preferred Skills
- 5+ years of hands-on experience in building scalable ML systems or training large ML models.
- 1+ year of experience in AI engineering.
- Strong technical skills in coding, testing, and developing solutions for scale.
- Solid practical knowledge of ML, understanding ML theory, and familiarity with the AI application lifecycle, especially in relation to foundation models from evaluation to deployment.
- A high sense of ownership and a proactive approach to delivering impact in a fast-paced and ambiguous environment.
About the Opportunity
- This is a full-time position.
- We offer a fully remote work environment (work from anywhere!).
You can learn more about us here.
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