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Embedded Machine Learning Jobs (NOW HIRING)

PROPRIUS

Senior Machine Learning Engineer

New York, NY

$114K - $157K/yr

Expert level coding skills (Python, C++ at minimum) * 3+ years' experience working with machine learning in embedded applications: model quantization, fixed point neural networks (CNN and RNN)

Apple

Embedded ISP Engineer

San Diego, CA · On-site

... and machine learning techniques, all while contributing to the future of photography and ... Build drivers for advanced image processing pipelines in embedded systems, working with the latest ...

Gather AI

Principal Machine Learning Scientist

Explore next-generation perception capabilities, including embedded and on-prem inference optimization for new deployment targets What You'll Need * 10+ years of experience in machine learning or ...

TetraMem Inc

Senior Machine Learning Engineer

San Jose, CA · On-site

$200K - $280K/yr

Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions ... Strong hands-on experience in machine learning, with a focus on edge AI, on-device inference, and ...

Match Group

Machine Learning Engineer II

Palo Alto, CA · On-site +1

$114K - $156K/yr

Machine Learning Software Engineers who bridge the gap between research and production by ... are embedded in core Tinder user flows at scale. Where You'll Work: This is a hybrid role and ...

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Embedded Machine Learning information

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$70K

$153.4K

$174K

How much do embedded machine learning jobs pay per year?

As of Jun 24, 2026, the average yearly pay for embedded machine learning in the United States is $153,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $173,000.00 per year, depending on experience, location, and employer.

Will AI replace embedded programmers?

Embedded machine learning involves developing algorithms for resource-constrained devices, and while AI tools can assist with coding and optimization, embedded programmers are essential for designing, implementing, and maintaining these systems. AI is more likely to augment their work rather than fully replace them, especially given the need for specialized knowledge of hardware and real-time constraints.

Is embedded AI a good career?

Embedded machine learning involves developing AI models for hardware with limited resources, such as IoT devices and embedded systems. It is a growing field with demand for skills in hardware programming, C/C++, and AI frameworks, offering opportunities in industries like automotive, healthcare, and consumer electronics.

Is embedded systems still a good career in 2026?

Embedded Machine Learning remains a strong career in 2026 as industries increasingly adopt AI-powered devices and IoT solutions. Professionals with skills in hardware programming, real-time systems, and machine learning frameworks like TensorFlow Lite are in demand for developing intelligent embedded applications. Continuous learning and familiarity with microcontrollers, sensors, and embedded software development are essential for long-term growth in this field.

What engineers make $500,000?

Senior engineers in specialized fields such as embedded machine learning, AI, or data science can reach salaries of $500,000 or more, especially with extensive experience, advanced skills in programming and hardware, and leadership roles. High compensation often involves working in high-demand industries, with additional bonuses or stock options contributing to total earnings.

What are some common challenges faced by professionals working in embedded machine learning roles?

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.

What is an Embedded Machine Learning job?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

What are the key skills and qualifications needed to thrive in the Embedded Machine Learning position, and why are they important?

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

More about Embedded Machine Learning jobs
What cities are hiring for Embedded Machine Learning jobs? Cities with the most Embedded Machine Learning job openings:
What are the most commonly searched types of Embedded Machine Learning jobs? The most popular types of Embedded Machine Learning jobs are:
What states have the most Embedded Machine Learning jobs? States with the most job openings for Embedded Machine Learning jobs include:
What job categories do people searching Embedded Machine Learning jobs look for? The top searched job categories for Embedded Machine Learning jobs are:
Embedded Machine Learning jobs near you
Infographic showing various Embedded Machine Learning job openings in the United States as of June 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.
Mid-Level Machine Learning Engineer

Mid-Level Machine Learning Engineer

TetraMem Inc

San Jose, CA • On-site

$110K - $200K/yr

Full-time

Posted 22 days ago

Job description

Responsibilities:
  • Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing.
  • Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions.
  • Work closely with hardware and software teams to integrate ML models into production systems.
  • Research and implement state-of-the-art ML techniques to enhance model efficiency, latency, and power consumption for embedded AI applications.
  • Improve inference efficiency and model compression techniques, including quantization, pruning, and knowledge distillation.
  • Collaborate with cross-functional teams to drive innovation and contribute to the overall system architecture.
  • Provide technical leadership and mentorship to junior engineers.
  • Publish research findings, present at conferences, and contribute to open-source projects when applicable.

Requirements:
  • 5+ years of experience or PhD in Computer Science, Electrical Engineering, or related fields.
  • Strong experience in machine learning, with a focus on edge AI and lightweight model deployment.
  • Expertise in ML frameworks such as PyTorch, TensorFlow, JAX.
  • Proficiency in programming languages such as C/C++, Python, and experience with ML model optimization.
  • Ability to work independently and collaboratively in a fast-paced startup environment.
  • Ability to provide mentorship, technical guidance, and career development support to junior engineers and interns.

Experience in one or more of the following areas considered a strong plus:
  • Understanding of ML compiler and runtime design.
  • Experience working with tools such as Optimum, ONNX, TensorRT, TFLite/LiteRT, ncnn, or CoreML.
  • Familiarity with hardware acceleration techniques.
  • Experience in embedded system development.

Salary Range: $110,000 - $200,000 / year
TetraMem celebrates diversity and is committed to creating an inclusive environment for all employees. We are proud to be an Equal Opportunity Employer and welcome applicants from all backgrounds. Qualified candidates will receive consideration for employment without regard to race, color, religion, creed, sex, gender identity or expression, sexual orientation, national origin, ancestry, age, marital status, medical condition, disability, genetic information, military or veteran status, or any other characteristic protected by applicable federal, state, or local law.
TetraMem is committed to providing reasonable accommodations to qualified applicants with disabilities throughout the recruitment process. Applicants requiring accommodation may contact Human Resources for assistance.
To ensure a fair, consistent, and efficient hiring process, all candidates must apply through TetraMem's official ClearCompany Applicant Tracking System (ATS). Applications submitted through the ATS allow our hiring team to evaluate candidates using a standardized process and ensure timely communication throughout the recruitment process. To promote equal consideration for all applicants, applications submitted outside of the ClearCompany ATS, including direct emails, LinkedIn messages, or unsolicited submissions to employees, may not be reviewed or considered.
We encourage all interested candidates to apply through the official TetraMem Careers page.

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