Embedded Systems Engineer Jobs in Massachusetts
Embedded Systems Engineer jobs in Massachusetts are in strong demand, with the state ranking among the most active U.S. markets for this role across defense electronics, medical devices, robotics, and semiconductor design from entry-level firmware roles through principal engineer positions. The heaviest hiring concentrates in Greater Boston, the Route 128 technology corridor, and the Lowell-Woburn area, where employers such as Raytheon Technologies, Boston Scientific, and Analog Devices maintain large embedded engineering teams. The most sought-after specialties in Massachusetts listings are real-time operating systems, FPGA development, and safety-critical embedded software for regulated industries. Find a role that fits below and apply directly.
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Showing 5 of 16+ Embedded Systems Engineer jobs
About us
Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.
Embedded Systems Engineer
In this role you will develop computing systems for humanoid robots. This may span compute platform design (ARM, SoC, microcontrollers), firmware and BSP bring-up, and kernel-level Linux work. Work will focus on a robot payload that intakes LiDAR, camera, IMU, and tactile sensor information and then outputs joint manipulation and locomotion commands that let the robot stand, move, and use its hands. You will partner closely with the ML team building the robot's software brain, ensuring the compute platform can run their perception and manipulation models with the latency and throughput they need. The system is designed to operate across a diversity of humanoid robot platforms, so your work will generalize across different hardware rather than target a single robot. You will collaborate closely with the mechanical, electrical, and ML teams to build tightly integrated, safety-conscious solutions ready for deployment in the field.
What You Will Get To Do
1. Backpack Compute Platform
- Compute Platform Design: Design and select the embedded compute platforms (ARM, SoC, microcontrollers) that power the humanoid payload, balancing capabilities against SWaP constraints.
- Firmware & BSP Bring-Up: Write and customize bare-metal and RTOS firmware, board support packages (BSPs), and bootloaders for the humanoid payloads computing hardware.
- Kernel-Level Development: Work at the Linux kernel level to support real-time performance and reliable operation of the backpack's compute stack.
- Testing & Diagnostics: Conduct thermal profiling, power draw analysis, and latency measurement, and implement watchdogs and health checks for the compute stack.
2. Sensor & Actuator Drivers
- Perception & State Sensor Drivers: Adapt, integrate, and where needed develop drivers for cameras, LiDAR, and IMUs that feed the backpack's compute platform with real-time perception and state-estimation data.
- Motor, Joint & Tactile Drivers: Adapt, integrate, and where needed develop drivers for motors, joint actuators, and tactile sensors, supporting low-latency control and feedback for humanoid manipulation and locomotion.
- Communication & Timing: Bring up wired (Ethernet, CAN, GMSL, SPI, I2C) and wireless interfaces with deterministic timing (PTP, PPS) across the payload.
3. Manipulation & ML Integration
- ML Team Partnership: Partner closely with the ML team building the robot's software brain to ensure the compute platform meets their latency, memory, and throughput needs.
- Manipulation Data Pipeline: Build the data pipeline connecting camera, LiDAR, IMU, and tactile input to joint manipulation commands, from raw sensor capture through to actuator control.
- Edge ML Enablement: Support accelerated inference on the backpack so ML models can interpret sensor data and issue robot commands in real time.
- ROS/DDS Middleware: Expose driver and sensor data through ROS/ROS2 and DDS interfaces so the ML team's software brain can consume it in real time.
4. Cross-Platform Generalization & Collaboration
- Platform Abstraction: Design the backpack's compute and software architecture to generalize across a diversity of humanoid robot platforms.
- Cross-Team Collaboration: Work closely with mechanical, electrical, and sensor engineers to develop a tightly integrated backpack payload.
- Technical Leadership: Lead the technical direction of backpack compute development, from architecture decisions through implementation.
- Safety & E-Stops: Implement e-stop circuitry and safety monitoring on the backpack platform, laying the groundwork for functional safety as the fleet matures.
What You Have
- Education: B.S., M.S., or Ph.D. in Computer Engineering, Electrical Engineering, Robotics, or a related field.
- Experience Level: Minimum of 3+ years of hands-on experience with embedded systems. We welcome candidates across mid-level to senior and staff levels.
- Programming: Proficient in C++ and Python for embedded and application-level development.
- Embedded Systems Experience: Experience bringing up and customizing bare-metal and RTOS firmware, Linux kernel and device drivers, and board support packages (BSPs), across platforms such as Jetson or custom SBCs.
- Driver Development: Experience developing drivers for cameras, LiDAR, IMUs, tactile sensors, or motors, connecting sensors and actuators to embedded compute.
- ML/Edge Acceleration: Familiarity with GPU, TPU, or NPU offload and frameworks such as CUDA or TensorRT for edge inference, ideally supporting manipulation or perception models.
- Real-Time Communication Protocols: Hands-on experience with Ethernet, CAN/CAN-FD, SPI, I2C, UART, USB, or PCIe, wireless links, and timing protocols such as PTP.
- ROS & Middleware: Familiarity with ROS/ROS2 and DDS for exposing sensor and actuator interfaces to higher-level software.
- SWaP-Constrained Design: Experience designing compute hardware and firmware under tight size, weight, and power (SWaP) constraints, such as wearable or backpack-style payloads.
What Will Set You Apart
- Humanoid Robotics Experience: Experience developing embedded systems, firmware, or drivers for humanoid or other legged robot platforms.
- Manipulation & Robot Control Knowledge: Familiarity with joint manipulation, motor control, and how sensor data flows into robot commands such as standing or grasping.
- Kernel-Level Development: Experience with Linux kernel modules, device driver development, kernel-level debugging, PREEMPT_RT, and deterministic, low-jitter timing in production systems.
- Safety-Critical Systems: Experience implementing e-stop circuitry, safety monitoring, or other safety-critical embedded systems for robots operating near people. Experience with functional safety standards such as ISO 13849 or ISO 10218 for robots operating in human environments.
- ML Collaboration: Experience working directly with ML or perception teams to meet model latency, memory, and throughput requirements on embedded hardware.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Compensation
The salary range for this role is $135,000-$185,000. The actual offer for this position will be based on factors such as relevant experience, competencies, certifications, and how well the candidate meets the qualifications outlined above. Part of our compensation package also includes full benefits, equity, and generous time.
Field AI Onsite Work Philosophy
At Field AI, we believe the most effective way to collaborate and solve complex challenges is by working together in person. This is a fully onsite role, and candidates will be expected to work from our Irvine, CA office. In-person engagement is essential to our success, and we offer flexible working hours to support focus and work-life balance.
Why Join Field AI?
We are solving one of the world’s most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment. You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field, winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals.
Be Part of the Next Robotics Revolution
To tackle such ambitious challenges, we need a team as unique as our vision — innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We’re seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators. We are headquartered in always-sunny Irvine, Southern California and have US based and global teammates. Join us, shape the future, and be part of a fun, close-knit team on an exciting journey!
We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.
We are dedicated to fostering a diverse and inclusive workplace and encourage applicants from all backgrounds to apply.
About us
Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.
Embedded Systems Engineer
In this role you will develop computing systems for humanoid robots. This may span compute platform design (ARM, SoC, microcontrollers), firmware and BSP bring-up, and kernel-level Linux work. Work will focus on a robot payload that intakes LiDAR, camera, IMU, and tactile sensor information and then outputs joint manipulation and locomotion commands that let the robot stand, move, and use its hands. You will partner closely with the ML team building the robot's software brain, ensuring the compute platform can run their perception and manipulation models with the latency and throughput they need. The system is designed to operate across a diversity of humanoid robot platforms, so your work will generalize across different hardware rather than target a single robot. You will collaborate closely with the mechanical, electrical, and ML teams to build tightly integrated, safety-conscious solutions ready for deployment in the field.
What You Will Get To Do
1. Backpack Compute Platform
- Compute Platform Design: Design and select the embedded compute platforms (ARM, SoC, microcontrollers) that power the humanoid payload, balancing capabilities against SWaP constraints.
- Firmware & BSP Bring-Up: Write and customize bare-metal and RTOS firmware, board support packages (BSPs), and bootloaders for the humanoid payloads computing hardware.
- Kernel-Level Development: Work at the Linux kernel level to support real-time performance and reliable operation of the backpack's compute stack.
- Testing & Diagnostics: Conduct thermal profiling, power draw analysis, and latency measurement, and implement watchdogs and health checks for the compute stack.
2. Sensor & Actuator Drivers
- Perception & State Sensor Drivers: Adapt, integrate, and where needed develop drivers for cameras, LiDAR, and IMUs that feed the backpack's compute platform with real-time perception and state-estimation data.
- Motor, Joint & Tactile Drivers: Adapt, integrate, and where needed develop drivers for motors, joint actuators, and tactile sensors, supporting low-latency control and feedback for humanoid manipulation and locomotion.
- Communication & Timing: Bring up wired (Ethernet, CAN, GMSL, SPI, I2C) and wireless interfaces with deterministic timing (PTP, PPS) across the payload.
3. Manipulation & ML Integration
- ML Team Partnership: Partner closely with the ML team building the robot's software brain to ensure the compute platform meets their latency, memory, and throughput needs.
- Manipulation Data Pipeline: Build the data pipeline connecting camera, LiDAR, IMU, and tactile input to joint manipulation commands, from raw sensor capture through to actuator control.
- Edge ML Enablement: Support accelerated inference on the backpack so ML models can interpret sensor data and issue robot commands in real time.
- ROS/DDS Middleware: Expose driver and sensor data through ROS/ROS2 and DDS interfaces so the ML team's software brain can consume it in real time.
4. Cross-Platform Generalization & Collaboration
- Platform Abstraction: Design the backpack's compute and software architecture to generalize across a diversity of humanoid robot platforms.
- Cross-Team Collaboration: Work closely with mechanical, electrical, and sensor engineers to develop a tightly integrated backpack payload.
- Technical Leadership: Lead the technical direction of backpack compute development, from architecture decisions through implementation.
- Safety & E-Stops: Implement e-stop circuitry and safety monitoring on the backpack platform, laying the groundwork for functional safety as the fleet matures.
What You Have
- Education: B.S., M.S., or Ph.D. in Computer Engineering, Electrical Engineering, Robotics, or a related field.
- Experience Level: Minimum of 3+ years of hands-on experience with embedded systems. We welcome candidates across mid-level to senior and staff levels.
- Programming: Proficient in C++ and Python for embedded and application-level development.
- Embedded Systems Experience: Experience bringing up and customizing bare-metal and RTOS firmware, Linux kernel and device drivers, and board support packages (BSPs), across platforms such as Jetson or custom SBCs.
- Driver Development: Experience developing drivers for cameras, LiDAR, IMUs, tactile sensors, or motors, connecting sensors and actuators to embedded compute.
- ML/Edge Acceleration: Familiarity with GPU, TPU, or NPU offload and frameworks such as CUDA or TensorRT for edge inference, ideally supporting manipulation or perception models.
- Real-Time Communication Protocols: Hands-on experience with Ethernet, CAN/CAN-FD, SPI, I2C, UART, USB, or PCIe, wireless links, and timing protocols such as PTP.
- ROS & Middleware: Familiarity with ROS/ROS2 and DDS for exposing sensor and actuator interfaces to higher-level software.
- SWaP-Constrained Design: Experience designing compute hardware and firmware under tight size, weight, and power (SWaP) constraints, such as wearable or backpack-style payloads.
What Will Set You Apart
- Humanoid Robotics Experience: Experience developing embedded systems, firmware, or drivers for humanoid or other legged robot platforms.
- Manipulation & Robot Control Knowledge: Familiarity with joint manipulation, motor control, and how sensor data flows into robot commands such as standing or grasping.
- Kernel-Level Development: Experience with Linux kernel modules, device driver development, kernel-level debugging, PREEMPT_RT, and deterministic, low-jitter timing in production systems.
- Safety-Critical Systems: Experience implementing e-stop circuitry, safety monitoring, or other safety-critical embedded systems for robots operating near people. Experience with functional safety standards such as ISO 13849 or ISO 10218 for robots operating in human environments.
- ML Collaboration: Experience working directly with ML or perception teams to meet model latency, memory, and throughput requirements on embedded hardware.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Compensation
The salary range for this role is $135,000-$185,000. The actual offer for this position will be based on factors such as relevant experience, competencies, certifications, and how well the candidate meets the qualifications outlined above. Part of our compensation package also includes full benefits, equity, and generous time.
Field AI Onsite Work Philosophy
At Field AI, we believe the most effective way to collaborate and solve complex challenges is by working together in person. This is a fully onsite role, and candidates will be expected to work from our Irvine, CA office. In-person engagement is essential to our success, and we offer flexible working hours to support focus and work-life balance.
Why Join Field AI?
We are solving one of the world’s most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment. You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field, winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals.
Be Part of the Next Robotics Revolution
To tackle such ambitious challenges, we need a team as unique as our vision — innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We’re seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators. We are headquartered in always-sunny Irvine, Southern California and have US based and global teammates. Join us, shape the future, and be part of a fun, close-knit team on an exciting journey!
We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.
We are dedicated to fostering a diverse and inclusive workplace and encourage applicants from all backgrounds to apply.
See All 16 Embedded Systems Engineer Jobs in Massachusetts
Find roles in Massachusetts that match your experience and apply in just a few clicks.
Find JobsEmbedded Systems Engineer Jobs by City in Massachusetts
Where Massachusetts roles are concentrated, by current openings.
Embedded Systems Engineer Job Market in Massachusetts
A snapshot from current Massachusetts openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Manufacturing
- Science & Research
- Technology & Software
What Massachusetts Employers Look For
The qualifications that appear most often in embedded systems engineer jobs across Massachusetts.
- Bachelor's degree in electrical engineering, computer engineering, or a closely related field
- Proficiency in C or C++ for bare-metal and RTOS-based embedded development
- Experience with hardware-software integration including schematics, oscilloscopes, and logic analyzers
- Familiarity with communication protocols such as SPI, I2C, UART, CAN, or Ethernet
- Active or eligible U.S. security clearance preferred by many Massachusetts defense employers
- Experience with safety or regulatory standards such as IEC 62443, FDA 510k, or DO-178C
Embedded Systems Engineer Jobs in Massachusetts: Frequently Asked Questions
How do you become a embedded systems engineer in Massachusetts?
Massachusetts does not require a state-issued license to work as an embedded systems engineer. Most employers expect a bachelor's degree in electrical engineering, computer engineering, or computer science from an accredited institution. Candidates targeting defense or aerospace roles along the Route 128 corridor often pursue a Professional Engineer registration through the Massachusetts Board of Registration of Professional Engineers and Land Surveyors, though it is not universally required. Certifications in real-time systems, FPGA design, or functional safety strengthen applications considerably.
How much do embedded systems engineers make in Massachusetts?
Embedded systems engineers in Massachusetts earn a median of about $167,600 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $118,490 for the lowest 10% to over $258,880 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire embedded systems engineers in Massachusetts?
Employers hiring embedded systems engineers in Massachusetts right now include Draper, Formlabs, and STR, based on current listings on Migrate Mate as of August 2026. Massachusetts's deep concentration of defense primes, medical device companies, and semiconductor firms means openings appear consistently across a wide range of industries and team sizes.
Which Massachusetts cities have the most embedded systems engineer jobs?
Cambridge, Boston, and Woburn lead Massachusetts for embedded systems engineer openings. Greater Boston anchors demand through its dense cluster of defense contractors, medical device manufacturers, and university-affiliated research labs, while suburban Route 128 communities such as Waltham and Woburn host major corporate campuses for semiconductor and robotics companies that drive hiring outside the city core.
Are there remote embedded systems engineer jobs in Massachusetts?
Yes, but they're rare. Embedded systems engineering is fundamentally hands-on work requiring access to hardware prototypes, lab equipment, and test environments, which limits full remote roles. About 0% of embedded systems engineer openings tied to Massachusetts are remote or hybrid as of August 2026. The portions of the role most likely to accommodate remote arrangements are firmware code review, simulation, documentation, and software-only debugging tasks.
How can I get hired as a embedded systems engineer in Massachusetts with little or no experience?
The most realistic entry path is an internship or co-op secured through one of Massachusetts's major research universities, since employers like Raytheon Technologies, Analog Devices, and Boston Scientific run structured programs that convert student placements into full-time offers. Candidates without internship experience should target associate or junior embedded engineer roles at smaller defense subcontractors along Route 128, where hands-on exposure is prioritized over credentials. A portfolio of personal microcontroller or FPGA projects and familiarity with RTOS concepts meaningfully strengthens applications for these roles.
Where can I find and apply to embedded systems engineer jobs in Massachusetts?
You can find and apply to embedded systems engineer jobs in Massachusetts on Migrate Mate, which lists current Massachusetts openings across defense, medical devices, robotics, and semiconductor industries. Find roles that match your background and experience level and apply directly.
See All 16 Embedded Systems Engineer Jobs in Massachusetts
Find roles in Massachusetts that match your experience and apply in just a few clicks.
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