Machine Learning Engineer (Robotics)

TL;DR

Machine Learning Engineer (Robotics): Developing and scaling large-scale ML training systems for multimodal robotics data with an accent on distributed training pipelines and GPU optimization. Focus on maximizing GPU utilization, optimizing neural network architectures for high-dimensional sensor data, and building scalable data processing workflows.

Location: Remote (Must be based in the USA or Canada)

Compensation: $225K – $260K USD / $177k - $215k CAD

Company

hirify.global is reimagining city logistics with personable sidewalk robots designed for commercial deliveries to reduce congestion and support local businesses.

What you will do

• Design and maintain training systems for petabyte-scale multimodal datasets, including video and point cloud data.
• Identify and resolve bottlenecks in the training pipeline to maximize GPU utilization and reduce training time.
• Develop and refine neural network architectures suitable for autonomy tasks handling high-dimensional sequential sensor data.
• Implement scalable systems to preprocess, transform, and augment large robotics datasets.
• Collaborate with ML scientists to integrate new models, experiments, and training approaches into the production pipeline.
• Develop tools and workflows for experiment tracking and rapid model iteration.

Requirements

• Master’s or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical discipline.
• Minimum of 5 years of professional experience developing, training, and deploying ML models in production.
• Hands-on experience with distributed training frameworks across multiple GPUs or compute nodes.
• Strong programming skills in Python for implementing ML models and data pipelines.
• Solid knowledge of neural networks, optimization algorithms, loss functions, and training methodologies.
• Must be based in the USA or Canada.

Nice to have

• Experience with robotics or autonomous driving datasets involving LiDAR, radar, camera video, or telemetry data.
• Experience developing models that combine multiple data modalities into a unified learning system.
• Peer-reviewed publications or significant research contributions in ML or robotics.

Culture & Benefits

• Equity offers.
• Remote-first work environment.
• Opportunity to work with cutting-edge robotics, ML, and computer vision technology.
• Collaborative, agile, and diverse team culture.