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Embedded Ai Engineer Jobs (NOW HIRING)

E-Space

AI / Embedded ML Engineer

Saratoga, CA · On-site

$145K - $190K/yr

As an AI / Embedded Engineer, you will be responsible for the full lifecycle of AI/ machine learning on resource-constrained hardware. This includes data ingestion, model development, optimization ...

E-Space

AI / Embedded ML Engineer

Saratoga, CA · Hybrid

$145K - $190K/yr

As an AI / Embedded Engineer, you will be responsible for the full lifecycle of AI/ machine learning on resource-constrained hardware. This includes data ingestion, model development, optimization ...

Transparent Search Group

AI Engineer

Sunnyvale, CA · Hybrid

$225K - $300K/yr

You'll collaborate closely with cross-functional teams across data, embedded systems, and cloud ... AI engineering. Strong proficiency in Python and experience with TensorFlow, PyTorch, or similar ...

Motional

Senior Embedded Software Engineer

Las Vegas, NV · On-site +1

$118K - $155K/yr

If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you.

Motional

Senior Embedded Software Engineer

Boston, MA · On-site +1

$134K - $176K/yr

If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you.

SANS

AI Engineer -

Washington, DC · On-site

Working closely with the onsite AI Architect , this role is embedded directly alongside the Bank development squads configuring AI tooling, operating governance controls, and enabling developers ...

Motional

Senior Embedded Software Engineer

Pittsburgh, PA · On-site +1

$120K - $157K/yr

If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you.

Service Global, Inc

AI Engineer

Austin, TX · On-site

... embedded systems. For more than 15 years, customer have trusted us for our innovative problem ... AI Engineer Location: Remote - Skills: * Strong backend engineering in TypeScript/Node.js ...

h2o.ai

AI Engineer

Dallas, TX · On-site

$103K - $142K/yr

Founded in 2012, H2O.ai is on a mission to democratize AI. As the world's leading agentic AI ... This is a hands-on engineering role embedded within a customer-facing field team, meaning your work ...

h2o.ai

AI Engineer

Dallas, TX · On-site

$103K - $142K/yr

Founded in 2012, H2O.ai is on a mission to democratize AI. As the world's leading agentic AI ... This is a hands-on engineering role embedded within a customer-facing field team, meaning your work ...

Programmers.io

Java Full Stack AI Developer

Sunnyvale, CA · On-site

$61.50 - $79.50/hr

• Drive the adoption of embedded AI, moving beyond simple API calls to integrating local LLMs and vector databases into the application layer. Evangelize usage of AI tools to accelerate developer ...

Norbert Health

Applied AI Engineer

New York, NY · On-site

The position We're looking for an Applied AI Engineer to take our growing collection of foundation ... Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing * Transparent, mission-driven ...

Norbert Health

Applied AI Engineer

New York, NY · On-site

The position We're looking for an Applied AI Engineer to take our growing collection of foundation ... Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing * Transparent, mission-driven ...

Guild

AI Engineer

$109K - $156K/yr

This role involves designing, programming, and training complex algorithms that emulate human ... Seamlessly integrate AI models into existing software applications, employing API calls or embedded ...

Norbert Health

Applied AI Engineer

Brooklyn, NY

The position We're looking for an Applied AI Engineer to take our growing collection of foundation ... Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing * Transparent, mission-driven ...

Norbert Health

Applied AI Engineer

Brooklyn, NY

The position We're looking for an Applied AI Engineer to take our growing collection of foundation ... Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing * Transparent, mission-driven ...

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All JobsEmbedded Ai Engineer Jobs

Embedded Ai Engineer information

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$70K

$153.4K

$174K

How much do embedded ai engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for embedded ai engineer 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.

What is an Embedded AI Engineer?

An Embedded AI Engineer is a professional who designs, develops, and implements artificial intelligence (AI) algorithms and models directly onto embedded systems, such as microcontrollers or edge devices. Their work involves optimizing AI solutions to run efficiently on hardware with limited computing resources, power, and memory. They collaborate with hardware engineers and software developers to integrate machine learning, computer vision, or other AI functionalities into products like smart appliances, autonomous vehicles, or IoT devices. Their expertise helps bring intelligent features directly to devices, enabling real-time decision-making without needing constant cloud connectivity.

What is the difference between Embedded Ai Engineer vs Machine Learning Engineer?

CriteriaEmbedded Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's in Electrical Engineering, Computer Science, or related; knowledge of embedded systemsBachelor's or Master's in Computer Science, Data Science, or related; strong programming skills
Work EnvironmentEmbedded systems, IoT devices, hardware integrationData centers, cloud platforms, software development environments
Employer & Industry UsageConsumer electronics, automotive, IoT companiesTech firms, startups, research institutions
Common Search & ComparisonYesNo

Embedded Ai Engineers focus on integrating AI algorithms into embedded hardware and IoT devices, requiring knowledge of hardware constraints and embedded programming. Machine Learning Engineers develop models primarily for software applications and data analysis. While both roles involve AI, Embedded Ai Engineers specialize in hardware-software integration within embedded systems, whereas Machine Learning Engineers work on developing and deploying AI models in software environments.

What are the key skills and qualifications needed to thrive as an Embedded AI Engineer, and why are they important?

To thrive as an Embedded AI Engineer, you need expertise in embedded systems, AI/ML algorithms, programming languages like C/C++ and Python, and typically a degree in computer engineering or a related field. Familiarity with development tools such as TensorFlow Lite, ONNX, embedded Linux, and microcontroller platforms is essential, along with experience deploying AI models on resource-constrained devices. Strong problem-solving, collaboration, and communication skills help you work effectively in multidisciplinary teams and address real-world challenges. These skills ensure efficient integration of AI into embedded systems, enabling innovative, high-performance solutions for edge computing.

How does an Embedded AI Engineer typically collaborate with hardware and software teams during a project?

Embedded AI Engineers work closely with both hardware and software teams to ensure AI models are efficiently integrated into resource-constrained devices. They often collaborate with hardware engineers to optimize model performance based on device limitations like memory and processing power. At the same time, they coordinate with software developers to design efficient firmware and manage data pipelines. Regular cross-functional meetings and code reviews are common to address integration challenges and maintain alignment throughout the project lifecycle.
More about Embedded Ai Engineer jobs
What cities are hiring for Embedded Ai Engineer jobs? Cities with the most Embedded Ai Engineer job openings:
What states have the most Embedded Ai Engineer jobs? States with the most job openings for Embedded Ai Engineer jobs include:
What job categories do people searching Embedded Ai Engineer jobs look for? The top searched job categories for Embedded Ai Engineer jobs are:
Embedded Ai Engineer jobs near you
Infographic showing various Embedded Ai Engineer job openings in the United States as of May 2026, with employment types broken down into 95% Full Time, 1% Part Time, and 4% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.

AI / Embedded ML Engineer

E-Space

Saratoga, CA • On-site

$145K - $190K/yr

Full-time

Medical, PTO

Posted 24 days ago

Job description

Ready to make connectivity from space universally accessible, secure and actionable? Then you've come to the right place!
E-Space is bridging Earth and space to enable hyper-scaled deployments of Internet of Things (IoT) solutions and services. We are building a highly-advanced low Earth orbit (LEO) space system that will fundamentally change the design, economics, manufacturing and service delivery associated with traditional satellite and terrestrial IoT systems.
We're intentional, we're unapologetically curious and we're 100% committed to innovate space-based communications and deliver actionable intelligence that will expand global economies, protect space and our planet and enhance our overall quality of life.
As an AI / Embedded Engineer, you will be responsible for the full lifecycle of AI/ machine learning on resource-constrained hardware. This includes data ingestion, model development, optimization, and deployment on embedded devices. This role is critical for building reliable, low-power, real-time ML systems that operate at the edge.
In this role, you will leverage your expertise in sensor data processing, lightweight model design, embedded software, and hybrid LLM integration to deliver production-ready ML solutions on hardware.
This position will report to Head of Product Engineering, and you will work closely with hardware, firmware, software, and data teams. This position is based in Saratoga, CA.
What you will do:
  • • Data Ingestion and Pipeline Development
    • Design and build data ingestion pipelines from sensors including IMUs, accelerometers, gyroscopes, microphones, and other environmental sensors
    • Handle raw sensor data: cleaning, labeling, synchronization, and storage
    • Build tools to collect, version, and manage training datasets at scale
    • Model Development and Training
    • Develop and train ML models for classification, regression, anomaly detection, and signal processing tasks
    • Select appropriate model architectures for each problem and hardware target
    • Fine-tune pre-trained models for domain-specific tasks and data distributions
    • Design and run experiments to evaluate and compare model performance
    • TinyML and Embedded Deployment
    • Optimize models for deployment on microcontrollers and edge processors such as ARM Cortex-M, RISC-V, and DSPs
    • Apply quantization, pruning, and knowledge distillation to reduce model size and inference latency
    • Use frameworks including TensorFlow Lite Micro, Edge Impulse, ONNX Runtime, and ExecuTorch
    • Integrate ML inference into embedded firmware written in C, C++, or Rust
    • Profile and optimize memory usage, power consumption, and real-time performance
    • Hybrid LLM Integration
    • Design hybrid architectures that combine on-device lightweight models with LLM-based reasoning
    • Build pipelines that route tasks between edge inference and cloud or edge-hosted LLM components
    • Evaluate trade-offs in latency, accuracy, and power between on-device and LLM-assisted approaches
    • Software Embedding and Systems Integration
    • Write clean, well-tested embedded software that integrates ML inference into real-time systems
    • Work with RTOS environments such as FreeRTOS and Zephyr, as well as bare-metal firmware
    • Collaborate with hardware and firmware teams to co-optimize the full system stack
    • Documentation and Reporting
    • Document design decisions, pipeline configurations, model benchmarks, and deployment procedures
    • Prepare technical reports and presentations for internal teams and stakeholders
    • Stay current with developments in TinyML, embedded AI, and edge computing and bring relevant innovations into the team
    • Collaboration and Support
    • Work closely with cross-functional teams including hardware engineers, firmware developers, and data scientists
    • Provide technical support during hardware bring-up, system integration, and field testing
    • Participate in design reviews and contribute constructive feedback across the stack
    • >

What you bring to this role:
  • 2+ years of experience in machine learning engineering, with at least 2 years focused on embedded or edge ML
    • Strong background in signal processing, sensor data handling, and real-time system constraints
    • Hands-on experience with IMUs and other sensor types including accelerometers, gyroscopes, barometers, and microphones
    • Proficiency in Python for ML development using frameworks such as PyTorch, TensorFlow, or scikit-learn
    • Experience with C or C++ for embedded systems development
    • Solid understanding of model optimization techniques including quantization, pruning, and distillation
    • Experience deploying models with at least one embedded ML framework such as TFLite Micro, Edge Impulse, or ONNX Runtime
    • Strong understanding of memory-constrained and power-constrained environments
    • Excellent problem-solving skills and the ability to work independently and as part of a team
    • >

Bonus points for the following:
  • Experience with RTOS platforms such as FreeRTOS or Zephyr
    • Familiarity with MCU families including NXP, STM32, ESP32, or similar
    • Experience designing hybrid edge-LLM pipelines or integrating small language models on device
    • Background in feature extraction techniques such as FFT, filter banks, and wavelet transforms
    • Experience with hardware-aware neural architecture search or AutoML for edge targets
    • Familiarity with Rust for embedded or systems programming
    • Prior work on products in wearables, robotics, industrial sensing, or IoT
    • >

$150,000 - $225,000 a year
This is a full time, exempt position, based out of our Saratoga office. The total compensation packaged will be determined by various factors such as your relevant job-related knowledge, skills, and experience.
We are redefining how satellites are designed, manufactured and used-so we're looking for candidates with passion, deep knowledge and direct experience on LEO satellite component development, design and in-orbit activities. If that's your experience - then we'll be immediately wow-ed.
E-Space is not currently able to provide employment sponsorship for candidates who do not hold work authorization for the location of this role.
Why E-Space is right for you:
As a member of our team, you will play a crucial role in driving our success. Our team members have a strong sense of dedication and responsibility; this includes a strong commitment to our mission to create an entirely new suite of global capabilities to improve lives, business efficiencies and build a smarter planet. This means that there will be times when extra hours, including nights and weekends, may be needed to meet critical deadlines and mission goals. In return, we offer a dynamic work environment with opportunities for professional growth and development and the chance to make a meaningful impact in a high-growth industry.
We want you to make the most of your journey at E-Space. That's why we support and invest in the physical, emotional and financial well-being of our team members and their families. Some of what you can expect when working at E-Space:
• An opportunity to really make a difference
• Sustainability at our core
• Fair and honest workplace
• Innovative thinking is encouraged
• Competitive salaries
• Continuous learning and development
• Health and wellness care options
• Financial solutions for the future
• Optional legal services (US only)
• Paid holidays
• Paid time off
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.

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