AI Research Engineer (Robotics)

What You’ll Do

• Deploy deep learning models on edge devices and in the cloud for real-time inference
• Fine-tune models on proprietary datasets and manage dataset versioning, labeling, and evaluation
• Write high-quality C++ or Rust code for deterministic, low-latency execution
• Build cloud pipelines that process millions of images and video streams in near real time
• Perform model surgery in PyTorch and TensorRT, including pruning, quantization, and graph optimization
• Optimize GPU utilization, memory footprint, and inference throughput
• Build and maintain middleware for real-time IPC between perception, planning, and control systems
• Profile production systems to diagnose memory, compute, and concurrency bottlenecks
• Design rigorous evaluation loops to measure model accuracy, latency, and robustness in field conditions

What We’re Looking For

• Strong experience building real-time robotics systems that span software and hardware
• Experience deploying neural networks under strict latency constraints where milliseconds matter
• Deep understanding of GPU memory management, batching strategies, and compute optimization
• Strong debugging skills using profilers and low-level performance tools
• Solid experience with PyTorch; experience with TensorRT and ONNX is highly desirable
• Deep expertise in C++ preferred; strong Rust or Python experience also welcome
• Experience building production systems that must be reliable, observable, and fault-tolerant

Bonus Points

• Experience with vLLM, SGLang, or high-performance LLM inference engines
• Experience deploying multimodal models or LLMs in robotics contexts
• Experience with distributed systems, structured logging, and observability at scale
• Familiarity with distributed pubsub, real-time Linux, or embedded GPU platforms
• Experience working with NVIDIA Jetson, CUDA kernels, or custom accelerators

Skills and Qualifications

• BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, or a related technical field
• 3+ years of experience building robotics, perception, or real-time systems (startup or high-performance production environments strongly preferred)
• Strong programming skills in C++ (preferred) with experience in Rust or Python
• Experience deploying deep learning models in production, particularly in environments with strict latency constraints
• Hands-on experience with PyTorch for training, fine-tuning, and modifying deep learning models
• Experience deploying models to edge devices or embedded systems where compute and memory resources are constrained
• Strong debugging and profiling skills using low-level performance tools and system profilers
• Experience building reliable, observable, and fault-tolerant production systems