Dynamo AI Verified
Artificial Intelligence, Defense & Space, Government Technology, Machine Learning, Computer Vision
ML Research Engineer Intern – Dynamo Guard / Dynamo Eval / AgentWarden
New York, New York, United StatesRemoteInternshipJunior / Entry-level$3,500–$5,000 /yrPosted 2 months agoVisa sponsorship availableHidden Gem · YC Startup
Role summary
Dynamo AI is seeking an ML Research Engineer Intern to work on advanced evaluation, guardrailing, and agent security mechanisms for their Dynamo Guard, Dynamo Eval, and AgentWarden products. This role involves designing, prototyping, and deploying ML-driven features and optimizing LLM evaluation pipelines. Responsibilities include building scalable components in a Kubernetes environment, implementing automated testing and monitoring, and collaborating with research and product teams. The ideal candidate will have strong Python skills, familiarity with ML frameworks like PyTorch or TensorFlow, and an understanding of LLMs, agentic systems, or model evaluation techniques. Experience with cloud, APIs, or containerization is a plus.
At Dynamo AI, an ML Research Engineer Intern will work at the intersection of machine learning research and production systems. You will help design, prototype, and deploy advanced evaluation, guardrailing, and agent security mechanisms across Dynamo Guard, Dynamo Eval, and AgentWarden. This role blends hands-on engineering with applied ML experimentation in real-world enterprise environments.
### Responsibilities
* Design and implement ML-driven features across Dynamo Guard, Dynamo Eval, and AgentWarden.
* Build and optimize evaluation pipelines for LLMs and agentic systems, including attack simulations and red-teaming frameworks.
* Develop scalable components within our Kubernetes-based infrastructure to support secure and reliable ML deployment.
* Translate research prototypes into production-grade systems with strong performance and observability.
* Implement automated testing, benchmarking, and monitoring workflows for model safety and robustness.
* Collaborate closely with research and product teams to iterate quickly from experimentation to deployment.
* Contribute to internal tooling for model validation, guardrail enforcement, and runtime monitoring.
### 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 (e.g., PyTorch, TensorFlow).
* Understanding of LLMs, agentic systems, or model evaluation techniques.
* Experience with cloud environments, APIs, or containerized systems (Docker/Kubernetes) is a plus.
* Strong problem-solving mindset and eagerness to build production-quality ML systems.
### Responsibilities
* Design and implement ML-driven features across Dynamo Guard, Dynamo Eval, and AgentWarden.
* Build and optimize evaluation pipelines for LLMs and agentic systems, including attack simulations and red-teaming frameworks.
* Develop scalable components within our Kubernetes-based infrastructure to support secure and reliable ML deployment.
* Translate research prototypes into production-grade systems with strong performance and observability.
* Implement automated testing, benchmarking, and monitoring workflows for model safety and robustness.
* Collaborate closely with research and product teams to iterate quickly from experimentation to deployment.
* Contribute to internal tooling for model validation, guardrail enforcement, and runtime monitoring.
### 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 (e.g., PyTorch, TensorFlow).
* Understanding of LLMs, agentic systems, or model evaluation techniques.
* Experience with cloud environments, APIs, or containerized systems (Docker/Kubernetes) is a plus.
* Strong problem-solving mindset and eagerness to build production-quality ML systems.