Senior Software Engineer, AI/ML Platform

About Our Client

The organization develops commercially deployed humanoid robots designed to work alongside people in warehouses, manufacturing facilities, and distribution centers. By automating physical and repetitive tasks, its technology enables human workers to focus on more complex and higher-value activities. The organization combines established safety practices, real-world deployment data, and advanced robotics technology to expand human productivity and capabilities.

About the Opportunity

The Senior Software Engineer, AI/ML Platform architects and builds foundational infrastructure that enables AI and machine learning operations at fleet scale. This role supports AI and robotics teams in developing, evaluating, and deploying foundation models and robot policies by providing scalable, reliable, and developer-friendly ML platforms and tooling.

Responsibilities

• Design and implement ML platform components supporting data processing, model training, evaluation, and deployment.
• Develop reliable workflows integrating cloud computing, Kubernetes, automation, and machine learning infrastructure.
• Build and maintain core platform capabilities such as model registries, feature stores, and experiment tracking systems.
• Develop developer-facing APIs, command-line tools, and services that simplify machine learning workflows.
• Implement CI/CD pipelines supporting continuous model retraining, testing, validation, and delivery.
• Collaborate with ML engineers, robotics teams, research teams, and data engineers to translate technical requirements into scalable solutions.
• Integrate ML orchestration, metadata tracking, and experiment management with existing data platforms.
• Apply MLOps best practices for reproducibility, data and model lineage, rollback, monitoring, governance, and operational reliability.
• Improve the scalability, observability, and maintainability of machine learning infrastructure.
• Mentor junior engineers and contribute to cloud and ML platform architecture and roadmap discussions.

Requirements

• Minimum of 5 years of professional software engineering experience, including at least 2 years working with ML infrastructure, data platforms, or MLOps.
• Experience developing or operating ML platform capabilities such as experiment tracking, model registries, model deployment, and training infrastructure.
• Familiarity with ML orchestration and tracking tools such as MLflow, Weights & Biases, Airflow, or Kubeflow.
• Proficiency with cloud-native platforms such as AWS, Google Cloud, or Azure.
• Experience with containers, Kubernetes, and infrastructure-as-code practices.
• Experience processing or modeling multimodal data such as sensor logs, camera streams, or behavioral and robotics data.
• Strong software engineering and system design skills.
• Ability to collaborate effectively with research, data engineering, machine learning, and robotics teams.
• Strong problem-solving, communication, and technical leadership skills.

Pay and Benefits

• Anticipated base salary range: $197,000–$307,000 USD annually.
• 401(k) plan with a 6% company match.
• Stock options as part of the equity compensation package.
• Annual discretionary bonuses may be available for eligible roles.