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Embedded Machine Learning Engineer Jobs in Pasadena, CA

Voxelcloud

Machine Learning Engineer

Los Angeles, CA · On-site

MS degree in computer science, engineering, or mathematics * 2-3 years of relevant experience in building deep learning solutions for computer vision problems * Proficient with at least one major ...

Magnopus

Machine Learning Engineer II

Los Angeles, CA · On-site

$100K - $150K/yr

Magnopus is looking for a Machine Learning Engineer who thrives at the intersection of product innovation, real-time systems, and creative collaboration. In this role, you won't just build models ...

ZEFR

Senior Machine Learning Engineer

Marina Del Rey, CA

$112K - $154K/yr

We are hiring a Senior Machine Learning Engineer focused in ML Operations to be involved in designing and building large-scale applications and systems to acquire, process, and store multi-terabytes ...

Capgroup

Senior Machine Learning Engineer

Los Angeles, CA

$112K - $154K/yr

Access on-demand professional development resources that allow you to hone existing skills and learn new ones "I can succeed as a Machine Learning Engineer at Capital Group" We are seeking a strong ...

Capital Group

Senior Machine Learning Engineer

Los Angeles, CA · On-site

$112K - $154K/yr

Access on-demand professional development resources that allow you to hone existing skills and learn new ones "I can succeed as a Machine Learning Engineer at Capital Group" We are seeking a strong ...

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All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Pasadena, CA

Embedded Machine Learning Engineer information

See Pasadena, CA salary details

$76.4K

$167.3K

$189.8K

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

As of Jun 11, 2026, the average yearly pay for embedded machine learning engineer in Pasadena, CA is $167,311.00, according to ZipRecruiter salary data. Most workers in this role earn between $143,400.00 and $188,700.00 per year, depending on experience, location, and employer.

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

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What does an Embedded Machine Learning Engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What are some common challenges faced by Embedded Machine Learning Engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

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

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Pasadena, CA? For Embedded Machine Learning Engineer jobs in Pasadena, CA, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning Engineer jobs in Pasadena, CA look for? The top searched job categories for Embedded Machine Learning Engineer jobs in Pasadena, CA are:
What cities near Pasadena, CA are hiring for Embedded Machine Learning Engineer jobs? Cities near Pasadena, CA with the most Embedded Machine Learning Engineer job openings:
Embedded Machine Learning Engineer jobs near you
Senior Machine Learning Engineer, Reinforcement Learning - Egofold

Senior Machine Learning Engineer, Reinforcement Learning - Egofold

Snail Games USA

Beverly Hills, CA • On-site, Remote

$150K - $185K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 20 days ago

Job description

Senior Machine Learning Engineer, Reinforcement Learning - Egofold
About Snail Games USASnail Games strives to create the new high bar for gameplay experience in online gaming. We have been a global developer and publisher of digital entertainment since 2009 and are committed to pushing the boundaries of the industry.
About EgofoldEgofold is an AI initiative within Snail Games focused on intelligent agents, simulation, and AI-driven workflows for interactive products. It operates with startup-style speed and broad ownership, backed by an established game company, and is currently building practical prototypes while shaping its longer-term direction.
About the RoleWe are looking for a Senior Machine Learning Engineer with strong depth in machine learning and practical experience applying reinforcement learning and related methods to agent behavior and decision systems. This role is focused on the ML core of Egofold: designing experiments, training and improving models, shaping evaluation loops, and helping successful approaches become usable parts of the broader project.
This is not a siloed research role. The best candidates stay engaged through evaluation, iteration, and practical integration, and bring enough adjacent breadth to be effective in a small, collaborative team. We value curiosity, ownership, sound judgment, and respectful, low-ego collaboration.
Job Type: Full-TimeLocation: Hybrid - Los Angeles Area (1-2 in-office meetings per month)
Responsibilities
  • Design, train, and iterate on machine learning models for intelligent agents and decision-making systems, with an emphasis on reinforcement learning and related approaches.
  • Define and refine state representations, action spaces, reward structures, and evaluation criteria to improve agent behavior.
  • Build and improve practical experimentation and training workflows, including data generation, experiment tracking, and reproducibility.
  • Analyze results, debug model behavior, and make pragmatic tradeoffs between model performance, iteration speed, and system complexity.
  • Work closely with engineers and other partners to help integrate successful ML work into usable product systems.
  • Contribute thoughtful technical input on next-step experiments, tooling, and ML direction as Egofold continues to evolve.

Minimum Requirements
  • Strong foundation in machine learning, with hands-on experience building, training, and iterating on applied ML systems.
  • Professional or substantial project experience with reinforcement learning, agent-based systems, sequential decision-making, or closely related areas.
  • Strong Python skills and experience with modern ML frameworks such as PyTorch.
  • Experience designing experiments, evaluating model behavior, and improving results through systematic iteration.
  • T-shaped capability: deep machine learning expertise plus practical range across one or more adjacent areas such as simulation, evaluation, model integration, systems collaboration, or robotics-adjacent machine learning.
  • Strong problem-solving ability, sound judgment, and comfort working in ambiguous, fast-changing environments.
  • Respectful, low-ego collaborative style and willingness to work beyond a narrow specialty when the work requires it.

Nice to Have Any of the following are valuable, but we do not expect depth in every area:
  • Experience with reinforcement learning methods such as PPO, SAC, DQN, actor-critic, or related approaches.
  • Familiarity with simulation environments, multi-agent systems, game AI, or interactive agent behaviors.
  • Familiarity with C++, inference runtimes, or collaborating with engineers who deploy machine learning models into production systems.
  • Exposure to robotics, embodied AI, or embedded / on-device machine learning constraints.

Salary Range: $150,000 - $185,000 Annually
Why Join the Snail Games USA Team?
  • True focus on work/life balance
  • Paid company holidays, vacation, and separate sick leave
  • Medical, dental, vision, and Life/LTD
  • 401k with company match

Work Authorization Requirements
Applicants must be legally authorized to work in the United States at the time of application. This position does not offer visa sponsorship now or in the future (including H-1B).
Additional Information
As part of the Company's activities in video game development, publishing, and short-form video content creation, certain projects, discussions, or creative materials may include themes, visuals, language, or subject matter that some individuals could find mature, violent, sexual, graphic, or otherwise sensitive in nature (collectively referred to as "Mature Content"). Examples may include, but are not limited to, depictions or descriptions of combat, violence, adult themes or relationships, suggestive or satirical humor, or strong language. Employees are expected to engage with such material in a professional and creative context as part of their job duties.

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