Senior Solutions Architect, Robotics Foundation Model Training

About This Opportunity

Our talent team is representing a confidential technology organization at the forefront of physical AI and robotics foundation model development. We're seeking a Senior Solutions Architect to work hands-on with research and engineering teams building the next generation of multimodal AI systems for robotics applications.

This is a unique opportunity to operate at the intersection of cutting-edge AI research, large-scale distributed computing, and real-world robotic systems. You'll architect training workflows for vision-language-action models, world models, and other foundation models that power autonomous robotics platforms.

Responsibilities

• Design and optimize end-to-end training workflows for robotics foundation models including world models, vision-language-action models, and multimodal architectures
• Build proof-of-concepts, reference architectures, and automated workflows that accelerate model experimentation, benchmarking, and continuous improvement
• Scale pre-training, fine-tuning, and reinforcement learning workloads across multi-GPU and multi-node distributed systems while optimizing utilization, throughput, and memory efficiency
• Identify and resolve data pipeline bottlenecks across storage, networking, preprocessing, and data loading for multimodal datasets including video, sensor data, and trajectory information
• Collaborate with product and platform engineering teams to influence the roadmap for physical AI infrastructure and tooling

What We're Looking For

Required Qualifications:

• MS, PhD, or equivalent experience in Computer Science, Artificial Intelligence, Electrical Engineering, Computer Engineering, Robotics, or related field
• 5+ years of industry or research experience in deep learning, distributed computing, or large-scale model training
• Hands-on experience training or optimizing multimodal or foundation models (vision-language models, vision-language-action models, world models), ideally in robotics contexts
• Experience across the full AI model lifecycle: pre-training, supervised fine-tuning, reinforcement learning or other post-training methods, evaluation, and model optimization
• Strong expertise in distributed training techniques including data parallelism, model parallelism, pipeline parallelism, sharding, and checkpointing on multi-GPU or multi-node systems
• Proficiency with multimodal training frameworks such as PyTorch, JAX, or Hugging Face Transformers
• Experience building or optimizing high-throughput data pipelines for large-scale training, including storage bandwidth optimization, network throughput, and preprocessing operations (decoding, tokenization, batching)
• Strong communication skills with ability to collaborate effectively across researchers, engineers, and executives

Preferred Qualifications:

• Experience with robotics AI workloads including reinforcement learning in simulation environments and synthetic data generation
• Proficiency with profiling and optimization tools such as Nsight Systems, Nsight Compute, or PyTorch Profiler
• Demonstrated track record improving training efficiency and scaling performance on large compute clusters
• Experience building automated workflows for model evaluation, data analysis, or research acceleration
• Familiarity with modern robotics simulation platforms and foundation model training frameworks

How We Work With You

When you apply through Get A Job.ai, one of our experienced recruiters will review your background and schedule an initial screening conversation. We'll discuss your experience with foundation model training, distributed systems, and robotics applications in detail. If there's a strong match, we'll prepare and submit your profile to our client for consideration. Please do not attempt to contact the client directly, as all communication must flow through our recruiting team to ensure a coordinated process.

Location and Employment Details

This position is based in the United States. Specific work arrangements (remote, hybrid, or onsite) will be discussed during the screening process based on the client's requirements and your location.

Equal Employment Opportunity: Get A Job.ai is committed to inclusive hiring practices and does not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.