Description review

Engineering Internship

Chess.com · Remote · back to the listing

HR standards

51/100

needs work

Title ↔ description

68/100

needs work

Reads as

Machine Learning Engineer

89% confident

What this role officially is

data scientist — ESCO, the EU occupation classification

Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.

Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist

How others title the same work

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Startups

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  • Staff AI Engineer - Agent Architecture & Behavior Artisan

What the listing never says

  • 35 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

About You

Above all, you love chess and want to share it with the world! You also naturally resonate with a variable mix of the following qualities, and are eager to learn how all of these qualities can be foundational to your career:

• Multidisciplinary: ability to switch between relevant subject matter with relative ease.
• Resilient: high tolerance for ambiguity during initial discovery phases in projects.
• Ability to simplify: absorb inherent complexity within your projects, and cut through the complexity to offer more simplified solutions.
• Agile: able to maximize output/productivity + future-proof for further growth.
• Holistic understanding: see how the various parts work within the whole of a project, and how the overall project combines the distinct parts to achieve the high level goals; also see how the project fits within the greater whole of the company.
• Unorthodox thinker: find novel solutions to the limitations inherent in every technology.
• Logical and intuitive: adhere to logical thought processes while remaining in tune with your own intuition or gut feeling while steering and yielding from AI and Agents.

What you’ll do as an Intern

We currently have internship opportunities in two engineering focus areas, Product Engineering or AI/ML Engineering. For each area you’ll have an opportunity to work with a multidisciplinary team to design and build the best possible chess experience using the most relevant software or data engineering principles.

What you’ll do as a Product Engineer Intern

• Build features and optimize systems, scaling for a global top 100 website
• Contribute to technology, architecture, workflow, and design decisions
• Contribute to the team knowledge-base

What you’ll do as an AI/ML Intern

• Optimize data preprocessing and feature engineering pipelines
• Develop, train, and deploy ML models, and integrate them into Chess.com products
• Build AI applications powered by LLMs

Preferred Skills for All Internship Opportunities

• 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

Preferred Skills for Product Engineer Intern

• Training, relevant coursework or experience with:
•
• client side programming languages (HTML, CSS, Typescript, Swift, Kotlin)
• backend programming languages (Golang/Java/PHP preferred)
• web application frameworks
• relational databases (MySQL preferred)

Preferred Skills for AI/ML Engineer Intern

• Strong math foundation and understanding of traditional ML algorithms
• Training, relevant coursework or experience with:
•
• Python or another programming language (TypeScript/Go/Java preferred)
• ML libraries and frameworks such as scikit-learn or PyTorch
• LLMs/RAG/context engineering/evals/agentic patterns
• SQL (BigQuery, MySQL, Postgres, etc.)

About the Opportunity

• This is a full-time position
• We are 100% remote (work from anywhere!)
• This role is open to applicants who can work in the USA or Canada

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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 250M+ 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.

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 8 points (from 59 before penalties). Reviewed 25 Sep 2026.