Senior AI Software Engineer - Autonomous Systems

AMD
San Jose, Austin
Workplace: HybridFull timeFunction: Software EngineeringEducation: mastersSkills: ["Problem-solving","Collaboration","Communication","Attention to detail"]

Design and implement AI-driven software for autonomous systems, selecting and optimizing models for scalable, low-latency real-time performance across edge and cloud. Collaborate cross-functionally to integrate AI frameworks into production software stacks and improve inference pipelines. Lead best practices for deep learning, GPU-accelerated computing, model compression, and deployment. Profile and optimize end-to-end system performance while staying current on AI and autonomous systems technologies.

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FursaFursa
AMD
AMD
2 days ago

Senior AI Software Engineer - Autonomous Systems

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 3 hours agoStatus: Live

Job Summary

Design and implement AI-driven software for autonomous systems, selecting and optimizing models for scalable, low-latency real-time performance across edge and cloud. Collaborate cross-functionally to integrate AI frameworks into production software stacks and improve inference pipelines. Lead best practices for deep learning, GPU-accelerated computing, model compression, and deployment. Profile and optimize end-to-end system performance while staying current on AI and autonomous systems technologies.
Location: San Jose, Austin
Workplace: Hybrid
Employment Type: Full time
Job Function: Software Engineering
Seniority: Mid level

Key Responsibilities

  • •Select and optimize AI models for autonomous applications, ensuring scalability, low latency, and real-time performance across edge and cloud deployments.
  • •Collaborate with cross-functional teams to integrate AI frameworks into software stacks and optimize inference pipelines for real-world use cases.
  • •Provide technical leadership for AI software best practices, including deep learning frameworks, GPU-accelerated computing, model compression, and efficient deployment strategies.
  • •Analyze and optimize AI software stack performance by profiling end-to-end real-time inference and identifying bottlenecks for targeted improvements.
  • •Stay current on AI framework and foundation model trends, edge AI deployment, and autonomous systems integration, providing insights and recommendations.

Key Requirements

  • •Bachelor’s or Master’s in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field.
  • •Proven experience using AI frameworks such as PyTorch, TensorFlow, JAX, or ONNX Runtime for autonomous applications.
  • •Strong knowledge of model profiling, benchmarking, quantization, pruning, and distillation to optimize AI performance and efficiency.
  • •Deep expertise with ROCm or CUDA, including GPU kernel optimization and GPU memory management for AI inference and training.
  • •Experience profiling end-to-end AI system performance using tools such as NVIDIA Nsight, TensorRT, or Triton Inference Server.
Experience:Autonomous systemsEdge AIGPU-accelerated computing
Education:Master's in Electrical Engineer, Computer Engineering, Computer Science
Skills:Problem-solvingCollaborationCommunicationAttention to detail
Languages:English
Tech Stack:PyTorchTensorFlowJAXONNX RuntimeROCmCUDANVIDIA NsightTensorRTTriton Inference ServerROSROS2GPUGPU memory managementGPU kernel optimizationModel profilingQuantizationPruningDistillationModel compressionONNX

Company Brief

AMD
Designs and produces semiconductor products including CPUs, GPUs, and adaptive SoCs for consumer, enterprise, and embedded markets, competing across PCs, data centers, and gaming industries.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1969
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Glassdoor: 3.9
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