Senior ML Engineer - Robotics Autonomy & Scalable Training

ProfilHQ; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Serve Robotics is seeking an experienced ML engineer to design and scale large-scale training systems for multimodal robotics data in production. You will optimize distributed training pipelines, neural architectures, and data processing workflows to improve training efficiency and GPU utilization while collaborating with ML researchers and infrastructure teams.

Responsibilities include developing scalable training tools, managing petabyte-scale datasets, and accelerating model iteration.

Qualifications

• Master’s or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related field.
• Minimum of 5 years of professional experience developing, training, and deploying machine learning models in production environments.
• Hands-on experience training ML models across multiple GPUs or compute nodes with distributed training frameworks.
• Strong programming skills in Python for ML models, data pipelines, and training workflows.
• Solid knowledge of neural networks, optimization, loss functions, evaluation, and training methodologies.

Responsibilities

• Design and maintain training systems processing petabyte-scale multimodal datasets across large GPU clusters.
• Identify and resolve bottlenecks in the training pipeline to maximize GPU utilization and reduce training time.
• Work with ML team to develop neural network architectures for autonomy tasks handling high-dimensional sensor data.
• Create and adjust loss functions and training strategies for complex multimodal inputs.
• Configure, monitor, and maintain large-scale distributed training jobs across multiple machines and GPUs.
• Implement scalable systems to preprocess, transform, and augment large robotics datasets for model training.
• Collaborate with ML scientists and engineers to integrate new models and training approaches into production pipelines.
• Analyze training metrics, model outputs, and logs to guide improvements.
• Develop tools/workflows to run experiments, track results, and iterate on model ideas.

Skills

Python

Distributed training

Multi-GPU

Neural networks

Data pipelines

Education

Master’s or PhD in Computer Science or related field

Tools

PyTorch

TensorFlow

CUDA

Job description

Serve Robotics is seeking an experienced ML engineer to design and scale large-scale training systems for multimodal robotics data in production. You will optimize distributed training pipelines, neural architectures, and data processing workflows to improve training efficiency and GPU utilization while collaborating with ML researchers and infrastructure teams.

Responsibilities include developing scalable training tools, managing petabyte-scale datasets, and accelerating model iteration.