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Remote Embedded Ai Jobs in California (NOW HIRING)

Pano

Computer Vision Engineer

San Francisco, CA · On-site +1

$141K - $184K/yr

We are a team of more than 175 people working in a hybrid-remote environment across North America ... You will gain hands-on experience across modern computer vision, edge AI, embedded systems, and ...

VYNYL

Project Manager, Software Development

Los Angeles, CA · On-site +1

$100K - $160K/yr

A significant portion of our work involves cutting-edge AI and data initiatives, including AI ... Mainly remote work: seeking candidates in the greater Los Angeles area to mainly work remotely with ...

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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 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:

Remote Embedded Ai jobs near you
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.

Senior FP&A Manager (Los Angeles, CA)

Spin Technology

Los Angeles, CA • On-site, Remote

$150K - $165K/yr

Full-time

Re-posted 22 days ago

Job description

About Spin.AI

Spin.AI is a fast-growing cybersecurity startup protecting organizations from ransomware, data loss, and shadow IT across Google Workspace, Microsoft 365 and Atlassian environments. With a growing global footprint, Spin.AI is at an inflection point: scaling its revenue, expanding its team, and scaling its finance and accounting infrastructure. 
 
The Opportunity

The FP&A team at Spin is expanding to support the company’s next phase of growth. We're looking for someone who's ambitious, analytical, and eager to make an impact at a high-growth startup. If you're entrepreneurially minded (think like an owner) and energized by building systems, processes, and insights in a rapidly scaling business, we'd love to hear from you. This role reports to the SVP Finance and is based in our Glendale, CA office. 
Key Responsibilities:
  • Partner with CEO and SVP Finance on annual planning, capital allocation and M&A initiatives
  • Own the rolling forecast model, with a focus on driving ARR growth and GTM efficiency
  • Track key SaaS metrics (e.g., CAC, Net Retention, etc.) to help drive data-driven decision-making across the organization
  • Oversee the Financial Business Review (MBR/QBR) process, providing deep-dive analysis on Forecast vs. Actuals to identify risks and opportunities
  • Act as a "CFO for the Departments," embedded with leaders in Engineering, Product, Sales and Marketing to manage headcount planning and operating expenses
  • Prepare discussion materials in advance of key meetings (Board, executive team, etc.)
  • Drive process improvements and automation in FP&A workflows 
Qualifications:
  • 8+ years of progressive experience in Financial Planning & Analysis (Bonus: Prior investment banking or consulting experience)
  • Startup experience scaling financial operations (Bonus: SaaS or Cybersecurity)
  • Expert knowledge in Excel, with demonstrated experience building forecast models (Revenue, P&L, BS, CFS)
  • Strong communication skills – ability to tell a compelling story through data
  • Detail-oriented, self-starter and comfort with ambiguity
  • Deep understanding of GAAP accounting and reporting
  • Experience with key systems of record (Quickbooks, Salesforce, etc.)
  • Experience with BI/analytics software (Looker, etc.); Bonus: proficient in SQL
What we offer:
  • Base salary: $150,000 - $165,000  + 15% bonus
  • 100% coverage of dental, medical and vision insurance
  • 401k plan
  • Unlimited PTO and hybrid flexibility (3 days in Glendale office required)
  • Fitness & wellness reimbursement ($1,200 per year)
Why Spin.AI?
  • Forbes Named Spin.AI One of America's Best Startup Employers THREE Years in a Row (2024- 2026)
  • Work in a fast-moving, high-impact cybersecurity company recognized by Gartner, Forrester, and G2.
  • Collaborative, transparent culture – your ideas and experiments matter.
  • Direct impact: your work translates into real business growth and visibility.
  • Remote flexibility, growth opportunities, and performance-based rewards.

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.