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Senior Embedded Machine Learning Jobs (NOW HIRING)

Familiarity with embedded machine learning, real-time systems, or deploying machine learning on ... edge devices. * Background in adaptive modulation, beamforming, or cognitive radio techniques.

JB061509 - Sr Embedded SW & Control Engin

Irvine, CA · On-site

$133.10K - $174.40K/yr

Title: Sr Embedded SW & Control Engineer * No. of Positions: 5 * Location: Irvine CA * Experience ... Machines, Actuator Control, Motor Control, BMS, Power Sequencing, Supervisory Control, Fault ...

Senior Embedded Software Engineer

Austin, TX · On-site

$122.90K - $161.10K/yr

As a Senior Embedded Software Engineer, you will play a key role in designing, developing, and ... Applying next-gen technology, high-density storage and machine learning to solve today's complex ...

Senior Embedded Software Engineer

Austin, TX · Hybrid

$122.90K - $161.10K/yr

As a Senior Embedded Software Engineer, you will play a key role in designing, developing, and ... Applying next-gen technology, high-density storage and machine learning to solve today's complex ...

Senior Embedded Engineer

Redwood City, CA · On-site

$182K - $202K/yr

We are solving real-world problems leveraging robotics, machine learning and computer vision, among ... Position Summary The Senior Embedded Engineer drives hardware-firmware integration across multiple ...

Sr. Embedded Software Engineer Department: Engineering Employment Type: Full Time Location ... Foster an environment of continuous learning, improvement, and technical growth. What You'll Bring:

Embedded Engineer, Senior

Hills, MN · On-site

$119.40K - $156.50K/yr

... areas of 3D machine vision and semiconductor process measurement. Our sensors are deployed in ... A Senior Embedded/Firmware Engineer is responsible for the implementation of firmware for Nordson ...

Embedded Engineer, Senior

Minneapolis, MN

$129.40K - $169.60K/yr

... areas of 3D machine vision and semiconductor process measurement. Our sensors are deployed in ... A Senior Embedded/Firmware Engineer is responsible for the implementation of firmware for Nordson ...

Sr. Embedded SW Engineer

Palo Alto, CA

$145.80K - $191K/yr

Title: Sr. Embedded SW Engineer Location: Palo Alto, CA Duration: 2 Years Save Lives - Develop ... machines. Here are some highlights of this position: Design and develop Object Oriented real time ...

The Software Engineer supports the development, deployment, and scaling of Python-based backend services for a distributed, cloud-hosted embedded machine learning platform, requiring foundational ...

Senior Machine Learning Engineer

New York, NY

$114.30K - $157K/yr

Sr. Machine Learning Engineer Location: New York, NY Sponsorship: Yes Relocation: Yes Industry ... with machine learning in embedded applications: model quantization, fixed point neural networks ...

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Senior Embedded Machine Learning information

See salary details

$75.5K

$144.8K

$193.5K

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

As of May 31, 2026, the average yearly pay for senior embedded machine learning in the United States is $144,773.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,000.00 and $162,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Senior Embedded Machine Learning Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often backed by an advanced degree in computer science or electrical engineering. Familiarity with tools such as TensorFlow Lite, ONNX, and embedded hardware platforms (e.g., ARM Cortex-M, NVIDIA Jetson) is typically required. Strong problem-solving, project management, and communication skills distinguish top performers in this role. These capabilities are crucial for efficiently deploying optimized machine learning models on resource-constrained devices and effectively collaborating across multidisciplinary teams.

What are some common challenges faced by Senior Embedded Machine Learning Engineers when deploying models on edge devices?

Senior Embedded Machine Learning Engineers often encounter challenges such as optimizing model size and inference speed to fit within the limited computational resources and memory of edge devices. Balancing accuracy and performance while minimizing power consumption is critical, especially for battery-operated products. Additionally, integrating models with existing embedded software and ensuring reliable, real-time operation can require close collaboration with hardware and firmware teams. Staying current with advancements in model compression and hardware acceleration is also essential for success in this role.

What does a Senior Embedded Machine Learning engineer do?

A Senior Embedded Machine Learning engineer designs, develops, and optimizes machine learning models to run efficiently on resource-constrained embedded devices such as microcontrollers, IoT devices, and edge hardware. They are responsible for integrating ML algorithms with embedded systems, ensuring low latency and minimal power consumption. Their work often involves collaborating with hardware engineers and software developers to deploy intelligent features in products like smart sensors, wearables, and autonomous systems.

What is the difference between Senior Embedded Machine Learning vs Embedded Software Engineer?

AspectSenior Embedded Machine LearningEmbedded Software Engineer
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML and embedded systemsBachelor's in CS, EE, or related; strong programming skills in C/C++
Work EnvironmentDeveloping ML models for embedded devices, hardware integrationDesigning and implementing embedded software for devices
Industry UsageAI/ML-focused companies, IoT, consumer electronicsAutomotive, industrial, consumer electronics

While both roles involve embedded systems, Senior Embedded Machine Learning focuses on integrating ML models into hardware, requiring knowledge of AI and data science. Embedded Software Engineers primarily develop software for embedded devices, emphasizing firmware and system-level programming. The roles overlap in embedded environment skills but differ in their core focus on AI versus traditional software development.

What cities are hiring for Senior Embedded Machine Learning jobs? Cities with the most Senior 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 Senior Embedded Machine Learning jobs? States with the most job openings for Senior Embedded Machine Learning jobs include:

Sr Software Engineer, Embedded Machine Learning

Cariad, Inc.

Mountain View, CA

$146.30K - $191.70K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago


Job description

We are CARIAD, an automotive software development team with the Volkswagen Group. Our mission is to make the automotive experience safer, more sustainable, more comfortable, more digital, and more fun. To achieve that we are building the leading tech stack for the automotive industry and creating a unified software platform for over 10 million new vehicles per year. We're looking for talented, digital minds like you to help us create code that moves the world. Together with you, we'll build outstanding digital experiences and products for all Volkswagen Group brands that will transform mobility. Join us as we shape the future of the car and everyone around it.

Role Summary

The Sr Software Engineer, Embedded Machine Learning is responsible for designing, optimizing, and deploying machine learning models on high-performance embedded hardware platforms. This role focuses on translating machine learning models from training environments into production-ready implementations on embedded ML accelerators, including selection of efficient model architectures, quantization, runtime performance analysis, and functional validation.

The Sr Software Engineer, Embedded Machine Learning works independently on complex technical problems and collaborates closely with software, hardware, and systems teams to ensure reliable, real-time performance of machine learning workloads in production embedded systems.

Role Responsibilities

Embedded ML Development & Optimization

  • Design, train, and optimize machine learning models for execution on embedded ML accelerators
  • Quantize and convert machine learning models from training frameworks to embedded runtime environments
  • Analyze and optimize runtime performance to meet real-time and hardware constraints
  • Develop and maintain production-quality code and artifacts supporting machine learning deployment on embedded systems

Validation & Production Support

  • Verify functional correctness and performance of deployed models on target hardware
  • Debug and resolve performance and accuracy issues across the machine learning deployment pipeline
  • Collaborate with cross-functional teams to integrate machine learning models into embedded systems
  • Support deployed machine learning models in production, including performance monitoring, issue triage, and iterative improvement

Technical Collaboration & Continuous Improvement

  • Contribute to continuous improvement of machine learning workflows, tools, and best practices
  • Share technical knowledge and lessons learned with peers
  • Document model behavior, performance characteristics, and deployment considerations to support collaboration and long-term maintainability

Years of Experience

  • 6+ years of experience in machine learning, embedded systems, or performance-critical software development
  • Production experience deploying and optimizing ML models on embedded or constrained hardware platforms

Required Education

  • Bachelor's degree in Computer Science or Computer Engineering

Desired Education

  • Master's degree in Computer Science or Computer Engineering

Skills

  • Strong analytical and problem-solving skills applied to complex, real-time systems
  • Ability to work independently on complex technical problems with limited supervision
  • Clear written and verbal communication skills for collaborating with cross-functional partners
  • Strong attention to detail and commitment to production-quality outcomes
  • Demonstrated ability to learn new technologies and share knowledge with peers

Required Skills

  • Training modern machine learning networks, including transformer-based architectures, for high-performance embedded hardware accelerators
  • Quantization, deployment, and optimization of machine learning models for production embedded systems
  • Profiling, debugging, and optimizing runtime performance of machine learning workloads on embedded ML accelerators
  • Supporting machine learning models through deployment, validation, and iterative improvement on target hardware

Desired Skills

  • Experience with Qualcomm Hexagon NPUs
  • Experience working in ADAS or automotive embedded systems environments

Work Flexibility

  • Some on-site work with embedded hardware required, driving test car

Compensation

Salary range is dependent on factors such as geographical differentials, credentials or certifications, industry-based experience, qualification and training. In the city of Mountain View, CA, the salary range for this position is $181,414 - $249,046.

CARIAD, Inc. provides performance based merits and annual bonus along with a competitive benefits package. Benefits include medical, dental, vision, 401k with employer match and defined contribution plan, short and long term disability, basic life and AD&D insurance, employee assistance program, tuition reimbursement and student loan repayment plans, maternity and non-primary caregiver leave, adoption assistance, employee referral program and vacation and paid holidays. We also offer a unique vehicle lease program that covers registration and insurance fees.

CARIAD is an Equal Opportunity Employer.  We welcome and encourage applicants from all backgrounds, and do not discriminate based on race, sex, age, disability, sexual orientation, national origin, religion, color, gender identity/expression, marital status, veteran status, or any other characteristics protected by applicable laws.

Employment with Cariad Inc. is contingent upon the successful completion of this screening process. We emphasize the importance of compliance with export control and sanctions laws as a fundamental aspect of our operations. Our company is dedicated to adhering to these regulations to ensure the lawful and ethical conduct of our business activities. Employment with our company is contingent on either verifying U.S. citizenship or U.S. lawful permanent resident status or obtaining any necessary license or confirming the availability of an applicable exemption or license exception. You, the applicant, will be required to answer certain questions for export control purposes, and that information will be reviewed by compliance personnel to ensure compliance with federal law. Cariad Inc. may choose not to apply for a license or use an applicable license exception (if available) for such individuals whose access to export-controlled technology or software source code may require authorization and may decline to proceed with an applicant on that basis alone.

By submitting your application, you acknowledge and agree to participate in the export control and sanctions compliance screening process. Your cooperation in this matter is essential to our shared success and the integrity of our operations. Thank you for your understanding and commitment to upholding these important standards.