AI Engineer Jobs in San Jose, CA
AI Engineer jobs in San Jose sit at the center of Silicon Valley's most active hiring market, concentrated in North San Jose, Downtown, and the Santana Row corridor, with demand running deep in enterprise AI platforms, semiconductor R&D, and cloud infrastructure. Companies currently hiring include TikTok, Adobe, and Capital One. Find a role that fits below and apply directly.
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Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career.
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 ensure seamless integration of AI frameworks into software stacks, optimizing inference pipelines and model performance for real-world use cases.
- Provide technical leadership and guidance in AI software best practices, focusing on deep learning frameworks, GPU-accelerated computing, model compression, and efficient deployment strategies for autonomous systems.
- Analyze and optimize AI software stack performance, particularly in real-time inference, GPU-accelerated, and autonomous navigation environments, identifying bottlenecks and implementing targeted improvements.
- Stay updated with the latest trends and technologies in AI frameworks, foundation models, edge AI deployment and autonomous systems integration, offering insights and recommendations to continuously advance AI capabilities.
- AI Frameworks: Proven experience designing and implementing solutions using leading AI frameworks such as PyTorch, TensorFlow, JAX, or ONNX Runtime, with a focus on autonomous applications.
- AI Model Analysis & Optimization: Strong knowledge and hands-on experience with model profiling, benchmarking, quantization, pruning, and distillation techniques to optimize AI models for performance and efficiency.
- ROCm, CUDA & GPU Computing: Deep expertise in ROCm or CUDA programming, GPU kernel optimization, and GPU memory management for accelerating AI inference and training workloads.
- System Performance Analysis: Expertise in profiling and analyzing end-to-end AI system performance using tools such as NVIDIA Nsight, TensorRT, Triton Inference Server, or similar profiling and optimization platforms.
- Autonomous Systems: Experience deploying AI models within software stacks, including integration with ROS/ROS2, real-time systems, and edge AI hardware platforms (NVIDIA Jetson, etc.).
- Problem-Solving Skills: Excellent problem-solving skills and attention to detail in debugging complex AI model behavior, performance regressions, and hardware-software interactions.
- Collaboration and Communication: Ability to work collaboratively in a cross-functional team environment with strong written and verbal communication skills.
- Bachelor’s or Master’s in Electrical Engineer, Computer Engineering, Computer Science, or a closely related field
Location
- San Jose or Austin
#LI-BW2
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career.
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 ensure seamless integration of AI frameworks into software stacks, optimizing inference pipelines and model performance for real-world use cases.
- Provide technical leadership and guidance in AI software best practices, focusing on deep learning frameworks, GPU-accelerated computing, model compression, and efficient deployment strategies for autonomous systems.
- Analyze and optimize AI software stack performance, particularly in real-time inference, GPU-accelerated, and autonomous navigation environments, identifying bottlenecks and implementing targeted improvements.
- Stay updated with the latest trends and technologies in AI frameworks, foundation models, edge AI deployment and autonomous systems integration, offering insights and recommendations to continuously advance AI capabilities.
- AI Frameworks: Proven experience designing and implementing solutions using leading AI frameworks such as PyTorch, TensorFlow, JAX, or ONNX Runtime, with a focus on autonomous applications.
- AI Model Analysis & Optimization: Strong knowledge and hands-on experience with model profiling, benchmarking, quantization, pruning, and distillation techniques to optimize AI models for performance and efficiency.
- ROCm, CUDA & GPU Computing: Deep expertise in ROCm or CUDA programming, GPU kernel optimization, and GPU memory management for accelerating AI inference and training workloads.
- System Performance Analysis: Expertise in profiling and analyzing end-to-end AI system performance using tools such as NVIDIA Nsight, TensorRT, Triton Inference Server, or similar profiling and optimization platforms.
- Autonomous Systems: Experience deploying AI models within software stacks, including integration with ROS/ROS2, real-time systems, and edge AI hardware platforms (NVIDIA Jetson, etc.).
- Problem-Solving Skills: Excellent problem-solving skills and attention to detail in debugging complex AI model behavior, performance regressions, and hardware-software interactions.
- Collaboration and Communication: Ability to work collaboratively in a cross-functional team environment with strong written and verbal communication skills.
- Bachelor’s or Master’s in Electrical Engineer, Computer Engineering, Computer Science, or a closely related field
Location
- San Jose or Austin
#LI-BW2
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
See All 1,084+ AI Engineer Jobs in San Jose
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Find AI Engineer JobsAI Engineer Job Market in San Jose
Who's Hiring
- TikTok328
- Adobe74
- Capital One74
- AMD66
- Google66
Top Industries Hiring
- Technology & Software156
- Electronics & Hardware49
- Consulting & Professional Services25
- Retail8
- Artificial Intelligence8
AI Engineer Jobs in San Jose: Frequently Asked Questions
How do I get a ai engineer job in San Jose?
Target the employer clusters that define San Jose's AI market: enterprise software and cloud platforms in North San Jose, semiconductor and hardware AI in the Alviso and Great America corridors, and defense-adjacent AI firms near the airport. Candidates who combine production ML experience with familiarity in large-scale distributed systems stand out locally. Networking through San Jose-based tech meetups and AI research groups at nearby universities also opens doors that online applications miss.
Which companies hire ai engineers in San Jose?
Companies currently hiring ai engineers in San Jose include TikTok, Adobe, and Capital One, per current listings on Migrate Mate as of September 2026. San Jose's employer mix leans heavily toward established enterprise tech firms, semiconductor companies, and well-funded AI startups, many headquartered or with major engineering campuses directly within city limits.
Are there remote ai engineer jobs in San Jose?
Yes, though it depends on the role: model development, data pipeline work, and research-oriented positions tend to be remote-friendly, while roles tied to on-site hardware, robotics, or physical infrastructure are largely in-person. About 44% of ai engineer openings tied to San Jose are remote or hybrid as of September 2026, with hybrid arrangements most common among enterprise software and cloud AI teams based in North San Jose.
How can I get a ai engineer job in San Jose with little or no experience?
The most realistic entry path in San Jose is landing an associate or junior ML engineer role at a mid-size enterprise software company, where teams are large enough to mentor early-career hires. San Jose's concentration of AI-adjacent startups also creates openings for candidates who can show strong project portfolios from coursework or open-source work. Roles like data analyst, ML ops support, or AI QA engineer are common lateral entry points at local firms before moving into full AI engineering positions.
Which industries hire the most ai engineers in San Jose?
The sectors hiring the most ai engineers in San Jose are Technology & Software, Electronics & Hardware, and Consulting & Professional Services, based on current listings on Migrate Mate as of September 2026. San Jose's identity as Silicon Valley's core city means these industries maintain large, permanent engineering headcount locally rather than relying on remote or distributed teams.
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