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Remote Embedded Ai Jobs in California (NOW HIRING)

Our mission is to enable Agentic Analytics, where AI agents work alongside humans on a shared ... embedded applications. As a Product Engineer at Cube, you'll take product ideas from spark to ...

Headquartered in Sunnyvale, CA, and Munich, Germany, with remote team members across North America ... point AI compute cores, embedded memory, embedded RISC-V CPU cores, and high speed serial ...

Data Scientist

Santa Cruz, CA · Remote

$130K - $170K/yr

Fullpower-AI delivers a complete B2B IoT platform for AI-powered algorithms, remote contactless ... Optimize algorithms for running on embedded devices and in the cloud * Design and run experiments ...

Marketing Researcher

San Francisco, CA · On-site +1

$45 - $50/hr

Onsite or hybrid preferred; fully remote may be considered for candidates based in San Francisco ... The role will also support the team in exploring AI tools and documenting research best practices.

Strategy Director

San Francisco, CA · Remote

$173K - $214K/yr

... and AI. This is a high-output strategy role, not a planning function-we are looking for a driver ... You will operate as an embedded strategic advisor to the CEO, CFO, SVP of Corp Dev & IR, and the ...

Showing results 21-40

Remote Embedded Ai information

What is a remote embedded AI engineer?

A Remote Embedded AI engineer is a professional who develops and integrates artificial intelligence (AI) algorithms into embedded systems, such as IoT devices, sensors, or smart appliances, while working from a remote location. Their role involves optimizing AI models to run efficiently on hardware with limited resources, ensuring reliable performance and low power consumption. These engineers typically collaborate with cross-functional teams to deliver intelligent, connected products, leveraging skills in machine learning, software development, and embedded hardware. Working remotely allows them to contribute to global projects without being tied to a specific office location.

What are the key skills and qualifications needed to thrive as a remote embedded AI engineer?

To thrive as a Remote Embedded AI Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++, Python, or TensorFlow Lite, often supported by a degree in computer engineering or related fields. Familiarity with real-time operating systems (RTOS), edge AI development platforms, and version control tools such as Git is typically required. Strong problem-solving skills, effective remote communication, and self-motivation help you excel in collaborative yet independent work environments. These competencies are crucial for building efficient, innovative AI solutions on hardware platforms while ensuring seamless teamwork across distributed teams.

What are some common challenges faced by remote embedded AI engineers, and how can they be overcome?

Remote Embedded AI Engineers often encounter challenges such as limited access to hardware for testing, asynchronous communication with distributed teams, and integrating AI models within resource-constrained embedded systems. Overcoming these challenges involves utilizing remote debugging tools, setting up robust simulation environments, and maintaining clear, regular communication with team members. Collaboration platforms and thorough documentation help ensure smooth coordination, while staying updated on best practices in embedded AI can address technical limitations.

What is the difference between Remote Embedded Ai vs Remote Machine Learning Engineer?

AspectRemote Embedded AiRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in Computer Science, Electrical Engineering, or related fields; experience with embedded systemsBachelor's or higher in Computer Science, Data Science, or related fields; strong programming and statistical skills
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsCloud platforms, data centers, software development environments
Industry UsageConsumer electronics, automotive, industrial IoTTech companies, finance, healthcare, research
Common Search/ComparisonYesNo

Remote Embedded Ai professionals focus on developing AI algorithms for embedded hardware and real-time systems, often working with IoT devices and specialized hardware. In contrast, Remote Machine Learning Engineers primarily develop models in cloud environments for data analysis and prediction. While both roles require strong programming skills, Embedded Ai emphasizes hardware integration, whereas Machine Learning Engineers focus on scalable model deployment.

What are the most commonly searched types of Embedded Ai jobs in California?

The most popular types of Embedded Ai jobs in California are:

What are popular job titles related to Remote Embedded Ai jobs in California?

For Remote Embedded Ai jobs in California, the most frequently searched job titles are:

What job categories do people searching Remote Embedded Ai jobs in California look for?

The top searched job categories for Remote Embedded Ai jobs in California are:

What cities in California are hiring for Remote Embedded Ai jobs?

Cities in California with the most Remote Embedded Ai job openings:

Infographic showing various Remote Embedded Ai job openings in California as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Principal AI Performance Modeling Architect

Advanced Micro Devices, Inc

Santa Clara, CA • On-site, Remote

Full-time

Re-posted 1 hour ago


Advanced Micro Devices rating

8.6

Company rating: 8.6 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

27th of 159 rated electronics manufacturers


Job description


WHAT YOU DO AT AMD CHANGES EVERYTHING 

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.  Together, we advance your career.  



THE ROLE:

As a Principal Engineer, you will spearhead the next generation of AI infrastructure by defining GPU architecture specifications that enable massive model training at scale. Your expertise will drive 2-3x performance gains in both training and inference pipelines through innovative system design and optimization. You will champion the adoption of cutting-edge techniques across the engineering organization, from efficient attention mechanisms to advanced parallelization strategies. By establishing comprehensive best practices for distributed ML systems, you will create a framework that enables seamless scaling from single-GPU to thousand-GPU deployments.

THE PERSON:

You have a deep understanding of GPU microarchitecture, memory hierarchies, and their impact on large-scale ML workloads You are passionate about software engineering and possess leadership skills to drive sophisticated issues to resolution. You are able to communicate effectively and work optimally with different teams across AMD. 

KEY RESPONSIBILITIES:

  • Lead performance modeling and optimization for multi-trillion parameter LLM training/inference including Dense, Mixture of Experts (MoE) with multiple modalities (text, vision, speech)
  • Model/optimize novel parallelization strategies across tensor, pipeline, context, expert and data parallel dimensions
  • Architect memory-efficient training systems utilizing techniques like structured pruning, quantization (MX formats), continuous batching/chunked prefill, speculative decoding
  • Incorporate and extend SOTA models such as GPT-4, Reasoning models (Deepseek-R1), and multi-modal architectures
  • Collaborate with internal and external stakeholders/ML researchers to disseminate results and iterate at rapid pace.

REQUIRED EXPERIENCE:

  • Extensive and Senior experience optimizing large-scale ML systems and GPU architectures
  • Deep expertise in CUDA programming, GPU memory hierarchies, and hardware-specific optimizations
  • Proven track record architecting distributed training systems handling large scale systems
  • Expert knowledge of transformer architectures, attention mechanisms, and model parallelism techniques

PREFERRED EXPERIENCE:

  • PyTorch, CUDA, TensorRT, OpenAI Triton
  • Distributed systems: Ray, Megatron-LM
  • Performance analysis tools: NSight Compute, nvprof, PyTorch Profiler
  • KV cache optimization, Flash Attention, Mixture of Experts
  • High-speed networking: InfiniBand, RDMA, NVLink

ACADEMIC CREDENTIALS:

  • Bachelors, MS/PhD in Computer Science/Engineering or equivalent industry experience

LOCATION: Austin, Tx or Santa Clara, Ca strongly preferred; Remote is a possibility for the right candidate

This role is not eligible for visa sponsorship.

#LI-RL1



Benefits offered are described:  AMD benefits at a glance.

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.

Qualifications:

Benefits offered are described:  AMD benefits at a glance.

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.

Education:UNAVAILABLEEmployment Type: FULL_TIME

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