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Embedded Machine Learning Engineer Jobs in Santa Clara, CA

Machine Learning Engineer

Mountain View, CA ยท On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply ...

About the Role We are seeking a Machine Learning Engineer to help drive the development,optimizationand deploymentof Altera FPGA Compiler. In this role, you will work at the intersection of machine ...

We are seeking machine learning engineers to join our team full-time. As part of your role, you will help us build pipelines of data collection, data extraction, data filtering/synthetic data ...

They are seeking a Machine Learning Engineer to translate research into scalable solutions, collaborating with teams to architect robust systems and integrate AI-driven features into applications.

Lead Machine Learning Engineer

San Jose, CA ยท On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...

Lead Machine Learning Engineer

San Jose, CA ยท On-site

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

About the Role As a Machine Learning Engineer on the Drive team, you'll own machine learning systems end-to-end--from feature engineering and model development to experimentation, deployment ...

The Machine Learning Engineer will architect and develop high-performance AI systems, manage large-scale datasets, and translate state-of-the-art research into production-ready code while ...

Senior Machine Learning Engineer

Santa Clara, CA ยท On-site

$143K - $189K/yr

We are seeking the best Machine Learning Engineers with a background in computer vision, LiDAR ... Experience with model optimization for real-time inference on embedded or automotive platforms (e.g ...

Machine Learning Engineer

Pleasanton, CA ยท On-site

$110 - $150/hr

... with machine learning frameworks such as TensorFlow, Keras, and PyTorch. Knowledge of cloud platforms and technologies, specifically Microsoft Azure, is crucial. Experience in DevOps and MLOps ...

Machine Learning Engineer

Cupertino, CA ยท On-site

$143 - $264/hr

Description We are seeking an experienced Machine Learning Research Engineer to design and apply state-of-the-art research in machine learning for data-centric problems! Your responsibilities will ...

New

We are seeking the best Machine Learning Engineers with a background in computer vision, LiDAR ... Experience with model optimization for real-time inference on embedded or automotive platforms (e.g ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Senior Machine Learning Engineer

San Jose, CA ยท On-site

$200K - $280K/yr

Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions ... Engineering, Machine Learning, or related fields. * Must have prior experience managing a team ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Showing results 41-60

Embedded Machine Learning Engineer information

See Santa Clara, CA salary details

$82.2K

$180.1K

$204.4K

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

As of Aug 16, 2026, the average yearly pay for embedded machine learning engineer in Santa Clara, CA is $180,139.00, according to ZipRecruiter salary data. Most workers in this role earn between $154,400.00 and $203,200.00 per year, depending on experience, location, and employer.

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 the key skills and qualifications needed to thrive as an embedded machine learning engineer?

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 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 cities near Santa Clara, CA are hiring for Embedded Machine Learning Engineer jobs?

Cities near Santa Clara, CA with the most Embedded Machine Learning Engineer job openings:

Infographic showing various Embedded Machine Learning Engineer job openings in Santa Clara, CA as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $180,139 per year, or $86.6 per hour.

Machine Learning Engineer

Unitytech

Mountain View, CA โ€ข On-site, Remote

$117K - $152K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 14 days ago


Job description

The opportunity
Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company.

Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform enables large-scale model training, feature generation, and experimentation workflows that power production ML systems.

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply research-driven thinking to real-world machine learning problems.

You'll help build and evolve the infrastructure that powers training data generation, ML workflows, and distributed model training. Working closely with experienced engineers and researchers, you'll contribute to systems that ensure our ML pipelines are reliable, scalable, and efficient.

This role offers the opportunity to bridge research and production-translating advanced ideas into systems that operate at scale.

What you'll be doing

  • Build and maintain data pipelines that generate training datasets for machine learning models and experimentation
  • Contribute to infrastructure that supports distributed training workflows (e.g., PyTorch, Ray)
  • Work with workflow orchestration tools (e.g., Airflow, Flyte, or similar) to support multi-stage ML pipelines
  • Improve reproducibility and reliability through dataset validation, monitoring, and testing
  • Partner with ML engineers to support experimentation and model iteration
  • Help optimize performance and efficiency across data processing and training systems
  • Contribute to the evolution of our offline ML platform architecture as it scales

What we're looking for

  • Bachelor's degree in Computer Science, Machine Learning, Systems, or a related field
  • Strong foundation in machine learning systems, distributed systems, or large-scale data processing (through research or projects)
  • Experience with Python and working with data-intensive workloads
  • Familiarity with ML frameworks (e.g., PyTorch, TensorFlow) and/or distributed systems (e.g., Ray, Spark)
  • Experience (academic or applied) with data pipelines, model training workflows, or large datasets
  • Strong problem-solving skills and ability to translate research ideas into practical systems
  • Interest in building scalable, reliable infrastructure for machine learning
  • Nice to Have
  • Experience with workflow orchestration systems (Airflow, Flyte, etc.)
  • Exposure to large-scale data platforms (data lakes, warehouses, streaming systems)
  • Publications or research in ML systems, distributed systems, or related areas

Additional information

  • Relocation support is not available for this position
  • Work visa/immigration sponsorship is not available for this position

Base Salary Range: We determine the base salary range for this role based on your primary work location:

Mountain View, SF/Bay: $117,000 - $152,000 gross USD
Bellevue, Seattle, NYC, Remote CA: $104,100 - $135,300 gross USD

This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate's relevant experience, professional background, and skill set.


Benefits


At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.


Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.


While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program


Life at Unity


Unity [NYSE: U] is the world's leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D - closing the gap between ideas and reality. For more information, please visit www.unity.com.


Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.


Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.


This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.


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