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Machine Learning Engineer Jobs in Santa Rosa, CA

Cellular Data & Automation Engineer

Bodega Bay, CA · On-site

$171.60K - $302.20K/yr

Ability to leverage data science algorithms and machine-learning models to solve various kinds of ... proven programming skills using Python, Pandas, Matplotlib and other key related tools. Solid ...

Ability to leverage data science algorithms and machine-learning models to solve various kinds of ... proven programming skills using Python, Pandas, Matplotlib and other key related tools. Solid ...

As a Cellular Data & Automation Engineer, you will be at the center of the embedded 5G/4G/multimode ... Ability to leverage data science algorithms and machine-learning models to solve various kinds of ...

... and machine learning tools to drive innovation in healthcare. • Invent better ways to reduce ... Engineering, Computer Engineering, or a related field • A history of academic excellence or ...

As a Cellular Data & Automation Engineer, you will be at the center of the embedded 5G/4G/multimode ... Ability to leverage data science algorithms and machine-learning models to solve various kinds of ...

Software Engineer, DevOps

Bodega Bay, CA · On-site

$135K - $225K/yr

... Engineer to join our growing team and play a pivotal role in designing and building our platform ... Experience with event-driven data and machine learning infrastructure, including streaming ...

Sr Staff R&D Engineer

Nicasio, CA

$206.40K - $276.70K/yr

Job Posting Title: Sr Staff R&D Engineer Req ID: 10127968 The Skywalker Sound Development Group is ... You will architect, build, and optimize cutting-edge machine learning systems at scale-leveraging ...

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Showing results 1-20

Machine Learning Engineer information

See Santa Rosa, CA salary details

$34.4K

$140.8K

$211.6K

How much do machine learning engineer jobs pay per year?

As of Jun 2, 2026, the average yearly pay for machine learning engineer in Santa Rosa, CA is $140,787.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $169,500.00 per year, depending on experience, location, and employer.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What job categories do people searching Machine Learning Engineer jobs in Santa Rosa, CA look for? The top searched job categories for Machine Learning Engineer jobs in Santa Rosa, CA are:
What cities near Santa Rosa, CA are hiring for Machine Learning Engineer jobs? Cities near Santa Rosa, CA with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Santa Rosa, CA as of May 2026, with employment types broken down into 1% Internship, 52% Full Time, 45% Part Time, and 2% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $140,787 per year, or $67.7 per hour.
Machine Learning Performance Engineer

Machine Learning Performance Engineer

Keysight Technologies, Inc.

Santa Rosa, CA • On-site

$160.16K - $266.93K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago


Keysight Technologies rating

7.9

Company rating: 7.9 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

53rd of 138 rated electronics manufacturers


Job description

Overview

Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.

Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.

The AI Models and Data Science team at Keysight AI Labs is hiring a ML Performance Engineer to make our training and inference stacks as fast as the math allows. You'll own end-to-end performance: profiling training workloads on multi-GPU clusters, writing custom CUDA kernels and LibTorch C++ extensions for hot paths, and optimizing inference for embedding in production software where every millisecond matters.

This role sits at the intersection of ML, systems engineering, and HPC. You'll work directly with MLEs and data scientists driving the modeling work, and with the engineering teams shipping these models into Keysight products.


Responsibilities
  • Profile and optimize training workloads — multi-GPU scaling efficiency, throughput, memory footprint, mixed precision, gradient checkpointing tradeoffs
  • Profile and optimize inference for low-latency, high-throughput deployment — quantization, graph optimization, kernel fusion, runtime selection
  • Write custom CUDA kernels and LibTorch (PyTorch C++) extensions to accelerate hot paths in both training and inference
  • Build and maintain serving infrastructure using ONNX Runtime, TensorRT, and similar — including C++ integration paths for embedding models inside production software
  • Partner with MLEs and data scientists on perf-aware architecture choices; partner with product engineering on deployment, versioning, and monitoring
  • Establish performance SLAs and regression tests so models stay fast as they evolve

Qualifications
  • 4+ years in ML engineering, performance engineering, or HPC, with substantial production ML experience
  • Strong Python and C++ — including LibTorch / PyTorch C++ extensions in production
  • Hands-on experience optimizing both training and inference workloads (not just one)
  • CUDA experience required — comfortable profiling GPU code with Nsight and reasoning about occupancy, memory hierarchy, and kernel-level tradeoffs
  • Production deployment experience with ONNX Runtime, TensorRT, or equivalent inference runtimes
  • Solid software engineering fundamentals: testing, versioning, code review, monitoring
  • Experience with Docker and container-based deployment

Careers Privacy Statement
Keysight Technologies Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other protected categories under all applicable laws.

The level of role and salary will be based on applicable experience, education and skills; Most offers will be between the minimum and the midpoint of the Salary Range listed below.

California Pay Range: MIN $160,160- MAX $266,930

Note: For other locations, pay ranges will vary by region.

US Employees may be eligible for the following benefits:

- Medical, dental and vision

- Health Savings Account

- Health Care and Dependent Care Flexible Spending Accounts

- Life, Accident, Disability insurance

- Business Travel Accident and Business Travel Health

- 401(k) Plan

- Flexible Time Off, Paid Holidays

- Paid Family Leave

- Discounts, Perks

- Tuition Reimbursement

- Adoption Assistance

- ESPP (Employee Stock Purchase Plan)

Qualifications:
  • 4+ years in ML engineering, performance engineering, or HPC, with substantial production ML experience
  • Strong Python and C++ — including LibTorch / PyTorch C++ extensions in production
  • Hands-on experience optimizing both training and inference workloads (not just one)
  • CUDA experience required — comfortable profiling GPU code with Nsight and reasoning about occupancy, memory hierarchy, and kernel-level tradeoffs
  • Production deployment experience with ONNX Runtime, TensorRT, or equivalent inference runtimes
  • Solid software engineering fundamentals: testing, versioning, code review, monitoring
  • Experience with Docker and container-based deployment

Careers Privacy Statement
Keysight Technologies Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other protected categories under all applicable laws.

The level of role and salary will be based on applicable experience, education and skills; Most offers will be between the minimum and the midpoint of the Salary Range listed below.

California Pay Range: MIN $160,160- MAX $266,930

Note: For other locations, pay ranges will vary by region.

US Employees may be eligible for the following benefits:

- Medical, dental and vision

- Health Savings Account

- Health Care and Dependent Care Flexible Spending Accounts

- Life, Accident, Disability insurance

- Business Travel Accident and Business Travel Health

- 401(k) Plan

- Flexible Time Off, Paid Holidays

- Paid Family Leave

- Discounts, Perks

- Tuition Reimbursement

- Adoption Assistance

- ESPP (Employee Stock Purchase Plan)

Education:UNAVAILABLEEmployment Type: UNAVAILABLE

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