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Remote Embedded Ai Jobs in California (NOW HIRING)

Brex

Staff Product Manager, Embedded

San Francisco, CA · On-site +1

$280K - $350K/yr

As a perk, we also have up to four weeks per year of fully remote work! Responsibilities * Own the ... Use AI to simplify the developer experience and shorten the path from discovery to production.

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Workato

Embedded Account Executive

Palo Alto, CA · On-site +1

... and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the ... Quartz ranked us the #1 best company for remote workers Responsibilities We are looking for an ...

Agility Robotics

Senior Director, AI

Bodega Bay, CA · On-site +1

$257K - $402K/yr

Partner with Hardware and Robot Software leadership to ensure the sensor suite and embedded compute ... This is a fully remote role with the option to work hybrid if a commutable distance from our Salem ...

DataRobot

Agentic AI Intern

San Francisco, CA · Remote

Each AI Native Intern is embedded in a real team, working on real problems, and is expected to ... This is a fully remote position. The program runs approximately 6 months. WHAT YOU'LL DO: * Build ...

DataRobot

Agentic AI Intern

San Francisco, CA · Remote

Each AI Native Intern is embedded in a real team, working on real problems, and is expected to ... This is a fully remote position. The program runs approximately 6 months. WHAT YOU'LL DO: * Build ...

GDIT

AI Data Scientist

Los Angeles, CA · On-site +1

... PDFs, embedded images) for search or RAG use. * Proven ability to build AIpowered analytics ... a remote work model GDIT IS YOUR PLACE At GDIT, the mission is our purpose, and our people are at ...

Uniphore

Sr. Director, Delivery Management

Palo Alto, CA · Remote

$249K/yr

As AI becomes more powerful, every part of the enterprise that impacts the customer will be ... Define FDE engagement models: embedded on-site, remote retainer, and GSI co-delivery - matched to ...

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All JobsEmbedded Ai JobsRemote Embedded Ai JobsRemote Embedded Ai Jobs in California

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 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 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 are the key skills and qualifications needed to thrive as a Remote Embedded AI Engineer, and why are they important?

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 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:
Remote Embedded Ai jobs near you
Infographic showing various Remote Embedded Ai job openings in California as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

Staff Cloud Platform Software Engineer

Mainspring Energy

Menlo Park, CA • On-site, Remote

$162K - $190K/yr

Other

Re-posted 5 days ago

Job description

About Mainspring

Mainspring Energy manufactures and delivers fuel-flexible, low-emissions local power solutions that rapidly add new capacity and deliver reliable, affordable, and sustainable electric power. The company began commercial shipments of its Mainspring Linear Generators in 2020 and today has hundreds of megawatts in advanced development and field operations for leading Fortune 500 companies, data centers, and utilities. Mainspring also partners with global energy leaders including AEP, NextEra Energy Resources, Schneider Electric, and more.

The core values that ground our work, guide our decisions, and connect us together:

  • Pragmatic Optimism
  • Excellence without Ego
  • Proactive Collaboration

Job Overview

Mainspring Energy is reinventing distributed power generation with our Linear Generator - a fuel-flexible, ultra-low emissions platform delivering resilient, on-site power for commercial, industrial, and utility customers.

Now we're scaling our fleet.

We're looking for the right architect to own the cloud-to-field software ecosystem that powers, monitors, and optimizes our distributed energy assets. This is a rare opportunity to unify cloud, data, and embedded device software under one technical vision - and scale a platform that directly enables the energy transition.

This is industrial-grade, uptime-critical, hardware-connected software.

Responsibilities
  • Ingest and process real-time telemetry from thousands of generators at high speed
  • Enable secure monitoring, diagnostics, and control of remote devices at scale
  • Build infrastructure to enable updating software on remote embedded devices
  • When our software works, customers stay powered. When it doesn't, the stakes are real
Qualifications
  • You are a systems thinker who understands that software decisions impact physical infrastructure.
  • 7+ years in software engineering on production systems, including team technical leadership 
  • Experience with device-to-cloud architectures and telemetry pipelines
  • Experience with AWS, GCP, or Azure
  • Experience in distributed systems and cloud infrastructure
  • A reliability-first mindset - 99% uptime isn't good enough
  • Experience in Industrial IoT, energy systems, industrial automation, or fleet-scale device platforms a plus
$162,000 - $190,000 a year

This position is onsite at our Menlo Park HQ. The salary will be adjusted to reflect local market conditions based on employee location as well as the experience of the employee. Along with the base salary, Mainspring offers pre-IPO stock options + benefits.

Does your experience not meet all of our posted requirements? Studies have shown that some people are less likely to apply to positions unless they meet every listed requirement. At Mainspring, we are committed to building a diverse, inclusive, flexible, and collaborative environment, so if you want to help us transition the world to clean and affordable electricity, and don't meet all posted requirements for a particular role, we'd still love to hear from you. Mainspring can sometimes be flexible enough to shift responsibilities for the right person, or otherwise identify open or upcoming roles that may better fit your professional background.

In more traditional words, Mainspring Energy, Inc is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

This compensation and benefits information is based on Mainspring Energy's estimate as of the date of publication and may be modified in the future. We generally do not negotiate on salary once we have made an offer. The level of pay within the range will depend on a variety of job-related factors that may include location, relevant prior experience and/or education, or particular skills and expertise. New hires joining the company tend to be paid within the starting base pay range noted above, with opportunities to increase pay over time based on development of additional skills, competencies, and company-specific knowledge.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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