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Senior Embedded Machine Learning Jobs in Santa Clara, CA

Efficient Computer

Senior Compiler Engineer

San Jose, CA · On-site

$160K - $210K/yr

... Senior Compiler Engineer to join our growing team. The Compiler Engineer will contribute to the ... embedded machine learning (ML) system stack and TinyML applications to run on the world's most ...

Doist

Senior Compiler Engineer

San Jose, CA · On-site

$160 - $210/hr

... Senior Compiler Engineer to join our growing team. The Compiler Engineer will contribute to the ... embedded machine learning (ML) system stack and TinyML applications to run on the world's most ...

New

Expedia

Senior Machine Learning Scientist

San Jose, CA

$107K - $146K/yr

Senior Machine Learning Scientist The Senior Machine Learning Scientist is responsible for building and evaluating GenAI- and LLM-powered solutions and AI agents that improve post-booking customer ...

Nvidia

Senior Machine Learning Engineer

Santa Clara, CA

$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 ...

TEKsystems

Sr. Machine Learning Engineer

Menlo Park, CA · Hybrid

$70 - $85/hr

Senior Machine Learning Engineer (LLM Evaluation & AI Agents) Location: Menlo Park, CA (Hybrid) Employment Type: 6-Month Contract Compensation: $70.00-$85.00/hour (W-2) Help Advance the Next ...

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All JobsEmbedded Machine Learning JobsSenior Embedded Machine Learning JobsSenior Embedded Machine Learning Jobs in Santa Clara, CA

Senior Embedded Machine Learning information

See Santa Clara, CA salary details

$88.7K

$170K

$227.3K

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

As of Aug 21, 2026, the average yearly pay for senior embedded machine learning in Santa Clara, CA is $170,027.00, according to ZipRecruiter salary data. Most workers in this role earn between $145,600.00 and $190,800.00 per year, depending on experience, location, and employer.

What does a senior embedded machine learning engineer do?

A Senior Embedded Machine Learning engineer designs, develops, and optimizes machine learning models to run efficiently on resource-constrained embedded devices such as microcontrollers, IoT devices, and edge hardware. They are responsible for integrating ML algorithms with embedded systems, ensuring low latency and minimal power consumption. Their work often involves collaborating with hardware engineers and software developers to deploy intelligent features in products like smart sensors, wearables, and autonomous systems.

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

To thrive as a Senior Embedded Machine Learning Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often backed by an advanced degree in computer science or electrical engineering. Familiarity with tools such as TensorFlow Lite, ONNX, and embedded hardware platforms (e.g., ARM Cortex-M, NVIDIA Jetson) is typically required. Strong problem-solving, project management, and communication skills distinguish top performers in this role. These capabilities are crucial for efficiently deploying optimized machine learning models on resource-constrained devices and effectively collaborating across multidisciplinary teams.

What are some common challenges faced by senior embedded machine learning engineers when deploying models on edge devices?

Senior Embedded Machine Learning Engineers often encounter challenges such as optimizing model size and inference speed to fit within the limited computational resources and memory of edge devices. Balancing accuracy and performance while minimizing power consumption is critical, especially for battery-operated products. Additionally, integrating models with existing embedded software and ensuring reliable, real-time operation can require close collaboration with hardware and firmware teams. Staying current with advancements in model compression and hardware acceleration is also essential for success in this role.

What is the difference between Senior Embedded Machine Learning vs Embedded Software Engineer?

AspectSenior Embedded Machine LearningEmbedded Software Engineer
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML and embedded systemsBachelor's in CS, EE, or related; strong programming skills in C/C++
Work EnvironmentDeveloping ML models for embedded devices, hardware integrationDesigning and implementing embedded software for devices
Industry UsageAI/ML-focused companies, IoT, consumer electronicsAutomotive, industrial, consumer electronics

While both roles involve embedded systems, Senior Embedded Machine Learning focuses on integrating ML models into hardware, requiring knowledge of AI and data science. Embedded Software Engineers primarily develop software for embedded devices, emphasizing firmware and system-level programming. The roles overlap in embedded environment skills but differ in their core focus on AI versus traditional software development.

What are the most commonly searched types of Embedded Machine Learning jobs in Santa Clara, CA?

The most popular types of Embedded Machine Learning jobs in Santa Clara, CA are:

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

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

Senior Embedded Machine Learning jobs near you

Senior Compiler Engineer

Efficient Computer

San Jose, CA • On-site

$160K - $210K/yr

Full-time

Retirement

Posted 16 days ago

Job description

Efficient is developing the world's most energy-efficient general-purpose computer processor. Efficient's patented technology uses 100x less energy than state of the art commercially available ultra-low-power processors and is programmable using standard high-level programming languages and AI/ML frameworks. This level of efficiency makes perpetual, pervasive intelligence possible: run AI/ML continuously on a AA battery for 5-10 years. Our platform's unprecedented level of efficiency enables IoT devices to intelligently capture and curate first-party data to drive the next major computing revolution
We are seeking a Senior Compiler Engineer to join our growing team. The Compiler Engineer will contribute to the design and implementation of an embedded machine learning (ML) system stack and TinyML applications to run on the world's most energy-efficient programmable processor. This position is a unique opportunity to develop applications for cutting-edge hardware as part of a highly interdisciplinary team, helping to demonstrate the value of Efficient's breakthrough technology. If you are an engineer who wants to be part of an intensely skilled team and wants to have an immediate impact building the next generation of energy-efficient ML applications, we want to talk with you!
Key responsibilities
  • Develop new compiler features to improve overall hardware efficiency while maintaining programmability. These may relate to:
    - Efficient's new dataflow ISA
    - Memory analysis and ordering Hardware constraints such as timing and power consumption
    - Place-and-route of applications onto Efficient's fabric
    - Visualization
    - Programmer debugging tools
  • Write unit and integration tests to uncover functional- and performance-related compiler bugs.
  • Work with various machine-learning frameworks to compile models to our custom hardware.
  • Debug and fix functional and performance issues of the compiler system.
  • Collaborate with the hardware and physical design team to understand and improve hardware architecture and propose future improvements.
  • Work closely with the application development team to understand the problem domain and deliver optimized compiler solutions.
Required qualifications & experience requirements
  • 6+ years of experience with C++.
  • Bachelor's/Master's degree in CS or related field.
  • Familiarity with compiler frameworks such as GCC, LLVM, and/or MLIR.
  • Understanding of computer architecture and optimization.
  • Experience using industry standard development and debugging tools including GDB.
  • Strong attention to detail, good work ethic, ability to work on multiple projects simultaneously, and good communication skills.
  • Good problem solving skills.
Additional qualifications considered
  • Familiarity with FPGA-compilation and/or PnR algorithms.
  • Experience with verilog, system verilog, or VHDL.
  • Knowledge of computer architecture.

We offer a competitive salary for this role, generally ranging from $160,000 to $210,000, along with meaningful equity and comprehensive benefits. The final compensation package will be based on your experience and location, with some flexibility to ensure we align with the right candidate.
Why Join Efficient?
Efficient offers a competitive compensation and benefits package, including 401K match, company-paid benefits, equity program, paid parental leave, and flexibility. We are committed to personal and professional development and strive to grow together as people and as a company.

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