Machine Learning Systems Engineer, Tooling & Infrastructure, Optimus

Machine Learning Systems Engineer, Tooling & Infrastructure, Optimus

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What To Expect

As a Software Engineer for the Optimus team, you will build the tools and infrastructure to make and measure improvements to neural network architecture by building and automating scalable data and inference pipelines, ensuring data quality by building visualizing tools. We are building a Machine Learning Platform that automates the collection, processing, and evaluation of data, reducing manual overhead and accelerating the entire ML lifecycle. The systems you create will drive continuous data integration, automated evaluation, and rapid deployment—impacting how thousands of Humanoid Robots perceive and act in the real world every day.

Responsibilities

• Automate data, inference, and auto-labeling pipelines
• Build the tooling and infrastructure for reporting and visualizing model metrics and performance
• Manage, analyze, and validate training and test datasets
• Coordinate with the team managing the hardware cluster to maintain high availability and jobs throughput for Machine Learning
• Drive implementation of best practices and monitoring systems to proactively detect and address issues in production
• Build and improve Python training infrastructure for stable and faster training and validate PyTorch models

Qualifications

Benefits & Compensation

Expected Compensation : $140,000 - $420,000 annual salary + cash and stock awards + benefits. Pay offered may vary based on location, knowledge, skills, and experience. Details of participation in benefit plans provided with offer.

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