Engineering Intern building scalable chess products or AI/ML systems for Chess.com. Developing features, models, and LLM-powered applications with multidisciplinary teams.
Responsibilities
Work with a multidisciplinary team to design and build the best possible chess experience
Product Engineering: build features and optimize systems, scaling for a global top 100 website
Product Engineering: contribute to technology, architecture, workflow, and design decisions
Product Engineering: contribute to the team knowledge-base
AI/ML Engineering: optimize data preprocessing and feature engineering pipelines
AI/ML Engineering: develop, train, and deploy ML models
AI/ML Engineering: integrate ML models into Chess.com products
AI/ML Engineering: build AI applications powered by LLMs
Requirements
Love chess and want to share it with the world
Multidisciplinary; ability to switch between relevant subject matter
Resilient; high tolerance for ambiguity during initial discovery phases
Ability to simplify complex projects and offer simplified solutions
Agile; able to maximize output/productivity and future-proof for growth
Holistic understanding of projects and company goals
Unorthodox thinker who finds novel technology solutions
Logical and intuitive approach to AI and agents
Chess player
Sense of ownership and responsibility
Excellent communicator and team player
Degree-seeking student currently enrolled at a college or university or equivalent bootcamp
Product Engineering: training, relevant coursework, or experience with HTML, CSS, TypeScript, Swift, Kotlin, Golang, Java, PHP, web application frameworks, and relational databases, preferably MySQL
AI/ML Engineering: strong math foundation and understanding of traditional ML algorithms
AI/ML Engineering: training, relevant coursework, or experience with Python, TypeScript, Go, Java, scikit-learn, PyTorch, LLMs, RAG, context engineering, evals, agentic patterns, SQL, BigQuery, MySQL, or Postgres
Benefits
Fully remote work arrangement
Work from anywhere
Opportunity to work with a multidisciplinary team
Opportunity to contribute to technology, architecture, workflow, and design decisions
Opportunity to contribute to the team knowledge-base
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