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Embedded Machine Learning Engineer Jobs in Sunnyvale, CA

Machine Learning Engineer

San Francisco, CA ยท On-site

$200K - $280K/yr

  • Medical

  • Dental

  • Vision

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 ...

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

Machine Learning Engineer

San Mateo, CA ยท On-site

$100K - $300K/yr

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

Machine Learning Engineer

San Francisco, CA ยท 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 ...

BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...

Machine Learning Engineer

San Francisco, CA ยท On-site

  • Medical

  • Retirement

  • PTO

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 ...

Machine Learning Engineer

San Francisco, CA ยท On-site +1

  • Medical

  • Retirement

  • PTO

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 ...

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 ...

The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI systems, collaborate with data engineering and research teams, and influence core decisions around ...

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for multimodal AI systems, collaborating with data engineering and research teams to drive the technical ...

Machine Learning Engineer

Sunnyvale, CA ยท On-site

$150.40 - $277.60/hr

  • Medical

  • Dental

  • Retirement

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Machine Learning Engineer

Sunnyvale, CA

$150K - $277K/yr

  • Medical

  • Dental

  • Retirement

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Showing results 21-40

Embedded Machine Learning Engineer information

See Sunnyvale, CA salary details

$82.2K

$180K

$204.2K

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 Sunnyvale, CA is $180,019.00, according to ZipRecruiter salary data. Most workers in this role earn between $154,300.00 and $203,000.00 per year, depending on experience, location, and employer.

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

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 Sunnyvale, CA?

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

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

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

Infographic showing various Embedded Machine Learning Engineer job openings in Sunnyvale, CA as of July 2026, with employment types broken down into 1% As Needed, 69% Full Time, 27% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $180,019 per year, or $86.5 per hour.

Machine Learning Engineer

Poesis

San Francisco, CA โ€ข On-site

$200K - $280K/yr

Full-time

Medical, Dental, Vision

Re-posted 29 days ago


Job description

About Poesis
Whoever builds the leading intelligence for finance will create far more than returns. Poesis is the AI-native investment firm running autonomous agents that predict markets, construct portfolios, and manage risk. Our founders managed institutional capital at Capital Group ($3T AUM) and led enterprise ML at Goldman Sachs and Amazon. We're building a new type of firm, where live capital is the training ground for an intelligence that compounds with every signal.
About the Role
At Poesis, machine learning and artificial intelligence open the door to improved alpha discovery, higher quality decision-making and intelligent risk management. 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 investment decision-making across the platform. You'll work across the full machine learning lifecycle, from experimentation and model and agent development to deployment and iteration, with significant ownership over both research and production outcomes.
Responsibilities
  • Rapidly implement and iterate on machine learning models, signals and research ideas
  • Design and run experiments to evaluate and improve model and agent performance and investment impact
  • Build reproducible workflows for feature generation, training, validation and evaluation
  • Work with large-scale financial, fundamental and alternative datasets to identify predictive signals and improve model performance

Required Competencies
  • 5+ years experience as a Machine Learning Engineer, or related role
  • Prior experience at a frontier AI lab, agentic startup, leading hedge fund, big tech company, or similar
  • Strong Python and SQL skills, with experience working with large-scale datasets
  • Experience developing, evaluating and deploying machine learning models in production environments
  • Success building reproducible research workflows and experimentation frameworks
  • Familiarity with modern AI systems, including LLMs, evaluation frameworks, and agent workflows
  • Skill leveraging Claude Code, Codex, or other coding agents
  • BS/MS/PhD in Computer Science or a related field, or equivalent practical experience

Preferred Competencies
  • Experience developing ML and AI systems using financial, fundamental, alternative, or time-series datasets
  • Familiarity with quantitative investing, portfolio construction, or risk management
  • Experience with PyTorch or TensorFlow, and AI workflows for parsing financial documents (filings, transcripts)

Location
Hybrid: 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available.
Benefits
We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches in our Menlo Park office, commuter benefits, and more.
Current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees.
Working at Poesis
As an early team member, you'll help shape not just the product, but how the company operates. Your decisions will have lasting impact across the business. You'll build from first principles, with no legacy systems, or entrenched processes slowing you down. Our team is made up of people from elite companies and universities who are low ego, collaborative, and excited to build together.