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Senior Embedded Machine Learning Jobs (NOW HIRING)

Senior Embedded Engineer

Boston, MA · Hybrid

$134K - $176K/yr

We're searching for a Senior Embedded Engineer excited to join our embedded team, where we build ... You'll advance the firmware architecture behind our first-to-market smart water machine and drive ...

Senior Embedded Software Engineer at unspun We are looking for a hands-on, execution-driven Senior ... Reporting to Automation Lead, you'll own critical machine-control software that helps scale our ...

... of experience in embedded system development and optimization with application to a specific ... Applies Machine Learning knowledge to assist in extending training or runtime frameworks or model ...

Senior Embedded Software Engineer at unspun We are looking for a hands-on, execution-driven Senior ... Reporting to Automation Lead, you'll own critical machine-control software that helps scale our ...

Senior Embedded Software Engineer

Sunnyvale, CA · On-site

$145K - $190K/yr

The future of defense will be decided by those who field intelligent machines at scale. At Scout AI ... The Role We're looking for a Senior Embedded Software Engineer who is excited about working close ...

Senior Embedded Engineer

Boston, MA · On-site

$140 - $170/hr

You'll advance the firmware architecture behind our first-to-market smart water machine and drive ... We'll also ask how you're learning and experimenting with AI in your work. Growing our AI fluency ...

Showing results 41-60

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 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 Systems Engineer

Kratos Defense

Huntsville, AL

Full-time

Posted 15 days ago


Kratos Defense & Security Solutions rating

7.8

Company rating: 7.8 out of 10

Based on 10 frontline employees who took The Breakroom Quiz


Job description

Kratos Defense Rocket Support Services is seeking a senior embedded systems engineer to design, develop, integrate, and validate advanced embedded software and hardware systems for mission?critical applications. This role requires deep experience with real?time processing, embedded firmware, sensor integration, communication interfaces, and software architecture in constrained, performance?demanding environments. Ideal candidates will have a strong foundation in embedded software engineering across multiple processor families, hands?on experience with real?time operating systems, device drivers, and hardware?software integration, and a history of delivering reliable embedded systems across the full product lifecycle from concept development to field deployment.

The senior embedded systems engineer will collaborate closely with cross?disciplinary teams including electrical, mechanical, systems, and test engineering. They will support program execution through requirements analysis, embedded architecture design, system integration, test planning, troubleshooting, and documentation. Some travel may be required for customer interactions, integration events, or testing.

ESSENTIAL JOB FUNCTIONS:
• Develop embedded software architectures, firmware, and real?time control logic for sensor?driven and mission?critical systems across multiple processing platforms.
• Design, implement, and debug device drivers, communication protocols, and interfaces including serial, CAN, Ethernet, SPI, I2C, and RF transceivers.
• Integrate embedded applications with hardware components such as microcontrollers, DSPs, FPGAs, sensors, actuators, and power systems.
• Develop and maintain real?time software using bare?metal, RTOS?based, or Linux?based environments.
• Implement state machines, control loops, data acquisition modules, and system?level embedded behaviors.
• Support system?level integration including hardware bring?up, interface verification, troubleshooting, and performance tuning.
• Develop tools, scripts, and build systems to support firmware deployment, cross?compilation, and multi?target development.
• Perform analysis, simulation, and testing to ensure software robustness, timing performance, and reliability under diverse environmental and operational conditions.
• Lead technical investigations, root?cause analysis, and corrective actions for embedded system issues.
• Work closely with cross?functional engineering teams to support system requirements definition, trade studies, architecture decisions, and design reviews.
• Prepare technical documentation, design artifacts, test reports, and customer briefings.
• Mentor junior engineers in embedded development practices, tools, and engineering methodologies.


REQUIRED EXPERIENCE & JOB SKILLS:
• Extensive embedded software development experience in C, C++, and related languages.
• Experience with real?time operating systems, firmware development, and low?level hardware interaction.
• Strong background with microcontrollers, DSPs, and embedded processor architectures.
• Experience developing and integrating communication interfaces and protocols (UART, SPI, I2C, Ethernet, RF links).
• Demonstrated capability in sensor integration, signal acquisition, and system?level control logic.
• Knowledge of FPGA interaction, hardware abstraction, and mixed hardware/software environments.
• Experience with build systems, configuration management, debug tools, and code versioning.
• Ability to create detailed technical documentation, design artifacts, and verification plans.
• Strong analytical, troubleshooting, and system?level thinking skills.
• Ability to work collaboratively with multidisciplinary engineering teams and interface with customers or program leadership.

• Experience with RTOS environments such as QNX or similar
• Experience with FPGA-based subsystems and mixed HW/SW architectures
• Experience in sensor-driven data acquisition systems preferred
• Experience with RF System on a Chip (RF SoC), Direct RF or other RF enabled embedded systems

EDUCATION & EXPERIENCE:
• Bachelor's or master's degree in Electrical Engineering, Computer Engineering, Embedded Systems, or related field.
• 8+ years of professional experience in embedded software and systems engineering.
• Advanced graduate?level work or specialization in image processing, radar processing, controls, telecommunications, or embedded systems is beneficial.


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