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Remote Embedded Machine Learning Jobs in Santa Clara, CA

Data Scientist

Santa Cruz, CA ยท Remote

$130K - $170K/yr

The ideal candidate will have a strong background in machine learning and data science and a proven ... Optimize algorithms for running on embedded devices and in the cloud * Design and run experiments ...

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Remote Embedded Machine Learning information

See Santa Clara, CA salary details

$82.2K

$180.1K

$204.4K

How much do remote embedded machine learning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for remote embedded machine learning in Santa Clara, CA is $180,139.00, according to ZipRecruiter salary data. Most workers in this role earn between $154,400.00 and $203,200.00 per year, depending on experience, location, and employer.

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

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What is a Remote Embedded Machine Learning Engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

What is the difference between Remote Embedded Machine Learning vs Remote Data Scientist?

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are some common challenges faced by Remote Embedded Machine Learning Engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.
What are the most commonly searched types of Embedded Machine Learning jobs in Santa Clara, CA? The most popular types of Embedded Machine Learning jobs in Santa Clara, CA are:
What cities near Santa Clara, CA are hiring for Remote Embedded Machine Learning jobs? Cities near Santa Clara, CA with the most Remote Embedded Machine Learning job openings:
Data Scientist

Data Scientist

Fullpower Technologies

Santa Cruz, CA โ€ข Remote

$130K - $170K/yr

Full-time

Posted 25 days ago


Job description

Fullpower-AI delivers a complete B2B IoT platform for AI-powered algorithms, remote contactless biosensing together with end-to-end engineering services, and customization of software in the field of life sciences, health, and biotechnology. Fullpower's platform is vetted and deployed as a PaaS, backed by a patent portfolio of 135+ patents. Fullpower's key areas of expertise include contactless biosensing, remote monitoring, non-invasive sleep technology, and the development of new technologies for others in the life sciences and biotechnology fields. Fullpower's B2B PaaS customers are in medical solutions, remote-contactless biosensing, bedding solutions, wearable, and wellness services.

Fullpower is seeking a passionate, team-oriented, and self-motivated Data Scientist interested in working on our next generation of products and algorithms and modeling rich, biomedical sensor data with a view toward medical, health, and fitness outcomes.

The ideal candidate will have a strong background in machine learning and data science and a proven track record of deploying models and algorithms for real-world applications.

Job Responsibilities:

  • Work with health data and time-series sensor data
  • Connect biomedical sensor data with medical, health, and fitness outcomes
  • Research and development of machine learning algorithms and statistical models for non-invasive sleep tracking
  • Develop visualizations and tools for understanding and annotating data
  • Optimize algorithms for running on embedded devices and in the cloud
  • Design and run experiments and clinical trials
  • Processing, cleaning, and combining different data sources to create new datasets
  • Collaborate with an interdisciplinary team of scientists, engineers, mathematicians for quick deployment of solutions

Software skills:

  • Expertise in Python and packages such as numpy, pandas, scikit-learn
  • Experience with a deep learning framework such as Tensorflow, pyTorch, or equivalent
  • Experience working with databases including familiarity with SQL
  • Experience with Amazon Web Services (AWS) or Google Cloud
  • Experience with C++ is a plus

Leadership qualities:

  • Self starter
  • Strong interpersonal and communication skills

Education and Experience:

  • Experience applying data science and machine learning to real-world problems
  • Bachelor's degree or higher in Mathematics, Statistics, Physics, Computer Science, or equivalent
  • Graduate degree and/or 5+ years experience a plus

Additional Information:

  • Fullpower does not sponsor work visas - must already be authorized to work in the United States
  • The base salary range for this full-time position is $130,000 to $170,000, plus equity, plus benefits. Fullpower's salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education and training.
Employment Type: Full-Time