ML Research Engineer Intern - Guard & Eval (Remote)

Capitolis; United States; Hybrid; USD 39,060 - 55,800; Full time

Job summary

Capitolis seeks a motivated ML Research Engineer Intern to work on machine learning projects, where you will design and implement innovative features in Dynamo Guard and Dynamo Eval. Your role includes building evaluation pipelines, developing scalable solutions on Kubernetes, and translating research into production systems. Ideal candidates are pursuing a degree in Computer Science or related fields with strong Python skills and an interest in real-world ML applications. Locations include New York, San Francisco, and remote options.

Qualifications

• Currently pursuing or recently completed a degree in Computer Science, Machine Learning, AI, or related field.
• Strong programming skills in Python and familiarity with ML frameworks such as PyTorch and TensorFlow.
• Understanding of LLMs, agentic systems, or model evaluation techniques.

Responsibilities

• Design and implement ML-driven features across Dynamo Guard, Dynamo Eval, and AgentWarden.
• Build and optimize evaluation pipelines for LLMs and agentic systems.
• Develop scalable components within our Kubernetes-based infrastructure for secure ML deployment.
• Translate research prototypes into production-grade systems.
• Implement automated testing, benchmarking, and monitoring workflows.
• Collaborate closely with research and product teams.
• Contribute to internal tooling for model validation and monitoring.

Skills

Python

Machine Learning frameworks (e.g., PyTorch, TensorFlow)

Problem-solving

Cloud environments

Containerized systems (Docker/Kubernetes)

Education

Currently pursuing or recently completed a degree in Computer Science, Machine Learning, AI, or related field

Job description

Capitolis seeks a motivated ML Research Engineer Intern to work on machine learning projects, where you will design and implement innovative features in Dynamo Guard and Dynamo Eval. Your role includes building evaluation pipelines, developing scalable solutions on Kubernetes, and translating research into production systems. Ideal candidates are pursuing a degree in Computer Science or related fields with strong Python skills and an interest in real-world ML applications. Locations include New York, San Francisco, and remote options.