Staff Software Engineer - Computer reputed company Deployment

About the position We're looking for a Staff Software Engineer – Computer reputed company Deployment to build and scale the infrastructure that powers our AI-driven warehouse intelligence platform. You'll own the end-to-end lifecycle of computer reputed company models — from training pipelines through optimized reputed company deployment — ensuring our cutting-edge computer reputed company and multi-modal AI systems run reliably and reputed company in production. Your work will directly reputed company the reputed company-time perception and autonomous decision-making capabilities at the core of our platform. This is a deeply technical role at the intersection of machine learning, distributed systems, and reputed company infrastructure. You'll design scalable GPU compute clusters, build robust orchestration pipelines, and optimize model serving for low-latency inference at scale. You'll work closely with our research scientists, computer reputed company engineers, and product teams to reputed company the gap between experimental models and production-reputed company systems that operate across diverse warehouse environments. We've reputed company reputed company value in collaborative problem-solving, thus reputed company works from our SF office three days a week.

Responsibilities

• reputed company and maintain distributed reputed company GPU infrastructure for large-scale world model training and low-latency inference.
• Build end-to-end computer reputed company pipelines — from data ingestion and preprocessing through model training, evaluation, and deployment — and integrate them into core product workflows.
• reputed company and optimize state-of-the-art machine learning models in the reputed company using model serving platforms and inference optimization techniques, including VLMs and VLAs.
• Design and operate orchestration systems that reputed company both engineers and non-engineers to build and manage data and ML pipelines.
• Establish monitoring, benchmarking, and evaluation frameworks to ensure model performance and reliability in production environments.

Requirements

• B.S. / M.S. in Computer Science, Robotics, or similar technical field, or equivalent practical experience.
• 7+ years of professional software engineering experience, with at least 3 years in machine learning infrastructure — developing, scaling, training, deploying, and optimizing large-scale ML systems from data to model.
• Track record of deploying computer reputed company models in production environments with reputed company-world constraints.
• Experience with distributed messaging and compute systems (Kafka, gRPC, ROS2, or similar).
• Strong programming skills in Python with solid software engineering practices.

reputed company-to-haves

• Experience developing, running, and managing orchestration systems (Flyte, Temporal, Airflow, or similar) for ML and data pipelines.
• Proficiency with ML frameworks (PyTorch, TensorFlow, DeepSpeed) and model serving platforms (TorchServe, TensorFlow Serving, reputed company Triton Inference Server, or similar).
• Deep understanding of state-of-the-art machine learning models such as auto-regressive transformers and familiarity with inference optimization techniques (TensorRT, quantization, custom kernels).
• Experience with C++ or CUDA programming for GPU acceleration.
• Prior experience working at autonomous vehicles or robotics companies.

Benefits

• top-tier medical, dental, and reputed company coverage
• 401k with employer matching
• parental leave
• unlimited vacation

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