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Senior Embedded Machine Learning Jobs (NOW HIRING)

Peoplentech LLC

Sr. Embedded SW Engineer

Palo Alto, CA · On-site

$145K - $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 ...

Coreforce

Senior Embedded Engineer

Atlanta, GA · Hybrid

$119K - $156K/yr

Join Our Team as a Senior Embedded Engineer Company: Coreforce Location: Atlanta (Hybrid) Job Type ... Solid understanding of embedded systems fundamentals including real-time concepts, state machines ...

Peoplentech LLC

Sr. Embedded SW Engineer

Palo Alto, CA · On-site

$145K - $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 ...

Socket.dev

Senior Embedded Software Engineer

Boston, MA · On-site

$140 - $160/hr

As a Senior Embedded Software Engineer on the TVision Meter Platform team, you will help define the ... Deploy, optimize, and support multiple computer vision and machine learning models running ...

Coreforce

Senior Embedded Engineer

Atlanta, GA · On-site

$140K - $150K/yr

Join Our Team as a Senior Embedded Engineer Company: Coreforce Location: Atlanta (Hybrid) Job Type ... Solid understanding of embedded systems fundamentals including real-time concepts, state machines ...

Chefman

Machine Learning Engineer

Mahwah, NJ · On-site

From computer vision models that understand what is happening inside an oven to embedded AI systems that make real-time cooking decisions, you will help define how machine learning is applied within ...

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Senior Embedded Machine Learning information

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

As of Aug 21, 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 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 are the key skills and qualifications needed to thrive as a senior embedded machine learning engineer?

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 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:

Senior Embedded Machine Learning jobs near you

Senior Embedded Firmware Engineer

Connect Tech+Talent

Austin, TX • On-site, Remote

$118K - $156K/yr

Contractor

Re-posted 11 days ago

Job description

Job Description Senior Embedded Firmware Engineer Location: Austin, TX Experience: 10+ Years Employment Type: Contract Position Overview We are seeking a highly experienced Senior Embedded Firmware Engineer to join our team on a contract basis. The ideal candidate will have a strong background in embedded systems development, real-time operating systems, firmware architecture, and debugging. This role requires a seasoned engineer who can contribute independently to the design, development, and optimization of embedded software solutions.

Key Responsibilities Design, develop, and maintain embedded firmware for complex hardware platforms. Develop and optimize software for Silicon Labs-based processors and embedded systems. Implement and maintain robust software architectures using Finite State Machine (FSM) methodologies.

Work within Real-Time Operating System (RTOS) environments to develop reliable and high-performance applications. Debug, troubleshoot, and optimize firmware using GCC toolchains and GDB debugging tools. Collaborate with cross-functional teams including hardware, systems, and software engineers.

Develop and maintain build systems using CMake. Create technical documentation and support code reviews, testing, and validation activities. Contribute to software quality, performance improvements, and product reliability initiatives.

Required Qualifications Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field. 10+ years of hands-on experience in embedded firmware/software development. Strong experience with Silicon Labs processors and development environments.

Solid understanding of Real-Time Operating Systems (RTOS). Proficiency in C, C++, and Python programming languages. Strong experience working in Linux-based development environments.

Deep understanding of Finite State Machine (FSM) design and implementation. Extensive experience with GCC toolchains and GDB debugging. Experience with CMake build systems.

Strong analytical, troubleshooting, and problem-solving skills. Excellent communication and collaboration abilities. Preferred Qualifications Experience with Cursor AI development tools.

Familiarity with OpenSpec or similar specification/documentation frameworks. Prior experience working in distributed or remote engineering teams. Experience developing firmware for connected, IoT, or industrial embedded products.

Location Preferred: Austin, Texas Remote: Open to qualified candidates working remotely. This is an excellent opportunity for a senior-level embedded engineer to contribute to cutting-edge embedded systems and firmware development projects.

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