C

Comet

Tracks ML experiments, models, and artifacts

Full Stack Engineer

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • At least 3 years of full-stack development experience, preferably in AI or machine-learning domains.
  • Hands-on experience with AI-assisted coding environments, integrated development environments, and agent-based workflows such as Cursor, Windsurf, GitHub Copilot, Codex, or Claude Code.
  • Deep understanding of AI model capabilities, limitations, and appropriate use cases, including GPT-5, Claude, and Gemini.
  • Expertise in React, TypeScript, and modern web development practices.
  • Strong proficiency in Java and frameworks such as Dropwizard.
  • Knowledge of scalable database design and containerization.
  • Experience with tracing, monitoring, and evaluation systems.
  • Strong communication skills for working in a distributed, global team environment.
  • Ability to work in ambiguous environments and solve complex technical challenges.

Responsibilities

  • Build and ship features at a fast pace in a fast-moving AI development environment.
  • Develop and maintain observability tools for large language model applications and retrieval-augmented generation systems.
  • Create user interfaces for large language model tracing, evaluation dashboards, and production monitoring.
  • Build APIs and backend services to support real-time large language model application monitoring.
  • Collaborate with AI researchers and machine-learning engineers to implement evaluation methodologies.
  • Contribute to frontend components using React and TypeScript and backend components using Java.
  • Design and implement automated evaluation systems and large language model-as-a-judge capabilities.
  • Work on integrations with large language model frameworks and libraries.
  • Participate in open-source community engagement and technical documentation.

Desired Qualifications

  • Experience contributing to or maintaining open-source projects.
  • Understanding of large language models, retrieval-augmented generation systems, and AI application architectures.
  • Experience with model evaluation, prompt engineering, and large language model optimization.
  • Knowledge of distributed systems and high-throughput data processing.
  • Familiarity with machine-learning experiment tracking and model monitoring platforms.
  • Experience with DevOps practices and continuous integration/continuous delivery pipelines.
  • Understanding of AI safety, model security, and responsible AI practices.

About the Company

Comet

Tracks ML experiments, models, and artifacts

Comet.ml provides a platform for managing machine learning experiments and lifecycle from data to deployment. It tracks experiments, artifacts, metrics, and models with a Model Registry for keeping track of model versions ready for deployment. The platform integrates Experiment Management with full lineage, letting users see the history of data, training, and deployment, and monitors model performance over time to detect drift or data quality issues. The product targets data scientists, ML engineers, and organizations building and deploying ML models. The pricing is likely subscription or usage-based, charging for storage and features used. The main competitors are other ML lifecycle platforms and experiment trackers. Comet.ml aims to help teams manage ML experiments, track data and models, and maintain a clear history and performance view to improve deployment outcomes.

Company size
51-200
Company stage
Series B
Total funding
$74.8M
Headquarters
New York City, United States
Founded
2017

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