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Embedded Machine Learning Engineer Jobs in Pittsburg, CA

Job Title Machine Learning Engineer Job ID 20985 Location Work Mode Onsite About the Team Our ML Platform team builds intelligent systems that power recommendations, forecasting, ranking ...

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

We're looking for an exceptional Machine Learning Engineer to help build the systems that make this possible. In this role, you'll develop models, signals and evaluation frameworks that power ...

Machine Learning Engineer

San Francisco, CA · On-site

$225K - $300K/yr

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

We're hiring an Machine Learning Engineer as the volume and complexity of legal AI workflows in our system scale rapidly. As more firms rely on Eve to automate high-stakes legal work - from intake ...

About the Role We're looking for a Machine Learning Engineer to design, build, and deploy production-grade ML systems that power the next generation of Plenful's AI platform. You'll own the end-to ...

Machine Learning Engineer

Dublin, CA · On-site

$90 - $130/hr

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 ...

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

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 ...

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

About The Role We're looking for a Machine Learning Engineer to design, build, and deploy production‑grade ML systems that power the next generation of Plenful's AI platform. You'll own the ...

Maintain, monitor, and enhance deployed machine learning systems to ensure continuous improvement. * Collaborate with software engineers, data scientists, and product teams to integrate AI solutions.

Lead Machine Learning Engineer

San Francisco, CA · On-site

$120K - $159K/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 ...

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Embedded Machine Learning Engineer information

See Pittsburg, CA salary details

$77.8K

$170.5K

$193.4K

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

As of Sep 7, 2026, the average yearly pay for embedded machine learning engineer in Pittsburg, CA is $170,491.00, according to ZipRecruiter salary data. Most workers in this role earn between $146,200.00 and $192,300.00 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 are popular job titles related to Embedded Machine Learning Engineer jobs in Pittsburg, CA?

For Embedded Machine Learning Engineer jobs in Pittsburg, CA, the most frequently searched job titles are:

What job categories do people searching Embedded Machine Learning Engineer jobs in Pittsburg, CA look for?

The top searched job categories for Embedded Machine Learning Engineer jobs in Pittsburg, CA are:

What cities near Pittsburg, CA are hiring for Embedded Machine Learning Engineer jobs?

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

Infographic showing various Embedded Machine Learning Engineer job openings in Pittsburg, CA as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 26% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $170,491 per year, or $82 per hour.

Machine Learning Engineer

Indotronix International Corporation

Pleasanton, CA • On-site

Contractor

This job post has expired today. Applications are no longer accepted.


Job description

Machine Learning Engineer (Azure Focus) - Remote (PST)
[About the Role]
Join GAP as a Machine Learning Engineer and lead the development, deployment, and optimization of innovative AI solutions in a fully remote environment. This six-month contract opportunity is tailored for engineers with a passion for hands-on machine learning in Microsoft Azure production settings. Collaborate with talented teams to create real business impact by delivering robust, scalable models for enterprise applications.
[Responsibilities]
- Design, build, and deploy machine learning models using neural networks and NLP techniques to solve business challenges
- Manage the complete ML lifecycle: data preparation, model selection, training, evaluation, deployment, and ongoing performance monitoring
- Leverage Python and ML frameworks (TensorFlow, PyTorch, Keras) to develop, optimize, and maintain models
- Implement MLOps best practices, including CI/CD pipelines, model versioning, and automated retraining in Azure environments
- Collaborate cross-functionally with data scientists, engineers, and stakeholders to deliver production-ready AI solutions
- Utilize Azure Machine Learning, Azure DevOps, and Azure Databricks for end-to-end ML operations
[Required Skills and Experience]
- Proven track record developing and deploying machine learning models into Microsoft Azure cloud platforms
- Hands-on expertise with neural networks and NLP methods (text classification, sentiment analysis, entity extraction, chatbots, or language models)
- Advanced proficiency in Python; practical experience with R and SQL for data extraction and statistical modeling
- Deep understanding of supervised and unsupervised learning algorithms, model evaluation, and optimization
- Mastery of modern ML frameworks (TensorFlow, PyTorch, Keras) in production
- Demonstrable experience in MLOps: CI/CD for ML, model monitoring, version control, retraining, and production support
[Preferred Skills]
- Experience with Azure Databricks, Azure Functions, and Azure Pipelines
- Familiarity with containerization (Docker/Kubernetes) for scalable ML deployments
- Strong feature engineering and ML pipeline automation skills
[Benefits]
- 100% remote work-collaborate with a diverse team from anywhere within PST hours
- Opportunity for contract extension and career progression on impactful enterprise AI projects
- Exposure to best-in-class Azure ML infrastructure and enterprise DevOps practices
[How to Apply]
Excited to build and deploy cutting-edge AI solutions in Azure? Submit your resume now. Qualified candidates will be contacted for an initial screening and technical interview.

Indotronix logo

About Indotronix

Sourced by ZipRecruiter

In 1986, Indotronix established itself in the staffing space. 22 years later, Avani entered the scene, offering consulting and technology development. Finally, in 2016, the two joined forces to begin delivering talent across all areas, from Staffing to Consulting to unique platform development.

Industry

Recruiting and staffing services

Company size

1,001 - 5,000 Employees

Headquarters location

Rochester, NY, US