Agent Systems Evaluation & Data Engineer

Prime Intellect, Inc.; New York (NY); Hybrid; USD 150,000 - 300,000; Full time

Benefits offered by this job

Professional Development budget

Equity incentives

Remote work flexibility

Job summary

Prime Intellect, Inc. is seeking a customer-facing ML/AI Platform Engineer focused on agent development and scalable post-training methods. You will shape how advanced models are aligned, evaluated, deployed, and used in real-world workflows.

Responsibilities include prototyping agents, building distributed pipelines, and integrating data-driven evaluation. Remote-friendly with equity incentives and a strong emphasis on research and practical impact.

Qualifications

• Strong background in machine learning engineering with post-training, RL, or model alignment.
• Experience with applied data workflows and evaluation frameworks for large models or agents.
• Deep expertise in distributed training/inference frameworks and scalable deployment.
• Experience deploying containerized systems at scale (Docker, Kubernetes, Terraform).
• Track record of research contributions in ML/RL (publications, OSS).

Responsibilities

• Prototype and iterate AI agents for automation, workflow orchestration, and decision-making at scale.
• Extend and integrate with agent frameworks to support evolving feature requests.
• Architect and maintain distributed training and inference pipelines for scalability.
• Develop observability and monitoring (Prometheus, Grafana) for production reliability.
• Translate customer insights into roadmap and research direction.
• Collaborate with RL and eval teams to align models with real-world signals.

Skills

ML Engineering

RL/ post-training

Distributed systems

Evaluation frameworks

Reliability & safety

Education

MS/PhD in CS/ML or related

Tools

Docker

Kubernetes

Ray

Terraform

Prometheus

Grafana

Job description

Prime Intellect, Inc. is seeking a customer-facing ML/AI Platform Engineer focused on agent development and scalable post-training methods. You will shape how advanced models are aligned, evaluated, deployed, and used in real-world workflows.

Responsibilities include prototyping agents, building distributed pipelines, and integrating data-driven evaluation. Remote-friendly with equity incentives and a strong emphasis on research and practical impact.