ML Engineer Jobs

Join a paid, remote talent pool building reinforcement-learning environments and evaluating AI agent behavior across software workflows. You’ll create trainable scenarios, connect tools, verify agent actions, and investigate execution failures.

Join an expert talent network designing reinforcement learning environments, verifiers, reward functions, and evaluation systems for AI agents. The remote role involves hands-on agent data work, trajectory grading, and contributor mentorship across project-based engagements.

Develop machine learning algorithms and scalable data capture systems that power next-generation Apple Health features. The role combines algorithm research, model evaluation, robotics-enabled data collection, and delivery of customer-facing solutions.

Senior Lead Software Architect owning end-to-end product capabilities, from architecture and implementation through delivery, while leading a small development team. The role combines full-stack cloud-native engineering with production AI/ML and model-serving architecture.

Build and operate the ML training and inference platform that brings generative image, video, and audio models to professional artists creating Prime Video and Amazon MGM Studios content. This role combines distributed ML systems, GPU optimization, model evaluation, and production reliability for the Nara creative platform.

Build and operate production machine learning systems across the full ML lifecycle at an early-stage AI recruiting technology company. The role combines model development, ML pipelines, deployment, monitoring, and production performance improvement.

Found the founding Machine Learning Engineer to build the ML function from the ground up, spanning post-training, agent systems, evaluation, and production infrastructure. This role combines hands-on ML engineering with roadmap ownership and technical leadership.

Build and operate the machine learning and data infrastructure powering OKX’s risk and fraud prevention systems. This hands-on role focuses on model serving performance, production ML platforms, distributed data pipelines, and reliable feature systems.