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Machine Learning Engineer Jobs in Santa Rosa, CA

Ema

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 ...

Atos SE

AI ENGINEER

Windsor, CA · On-site

$120 - $180/hr

Design, build, and deploy scalable machine learning solutions using Gemini Enterprise and Google ... Collaborate with data scientists, engineers, and business stakeholders to deliver production-ready ...

New

StaffGreat.com

Engineer (early career)

Santa Rosa, CA · On-site

They're hiring early-career engineers with raw ability rather than domain experience ... The role is deliberately broad: machine learning, geometry, graphics, and AI, spanning geometry and ...

New

StaffGreat.com

Engineer (early career)

Sonoma, CA · On-site

They're hiring early-career engineers with raw ability rather than domain experience ... The role is deliberately broad: machine learning, geometry, graphics, and AI, spanning geometry and ...

New

KenkoTech Futures

AI Scientist

Sonoma, CA · On-site

PhD in Machine Learning, Computer Science, Computational Biology, Bioinformatics, Statistics ... Strong programming skills using modern ML frameworks (PyTorch, JAX, etc.) * Experience with ...

KenkoTech Futures

AI Scientist

Santa Rosa, CA · On-site

PhD in Machine Learning, Computer Science, Computational Biology, Bioinformatics, Statistics ... Strong programming skills using modern ML frameworks (PyTorch, JAX, etc.) * Experience with ...

Apple

ML Agent Engineer

Bodega Bay, CA · On-site

$142K - $263K/yr

You will work in an organization of world-class machine learning researchers and engineers. Our work powers technologies across the Apple ecosystem and is published in the most selective scientific ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Santa Rosa, CA

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 Sep 5, 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 is a machine learning engineer?

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 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 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.

More about Machine Learning Engineer jobs

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

The most popular types of Machine Learning Engineer jobs in Santa Rosa, CA are:

What are popular job titles related to Machine Learning Engineer jobs in Santa Rosa, CA?

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

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:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Santa Rosa, CA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $140,787 per year, or $67.7 per hour.

Software Engineer, DevOps

Ema

Bodega Bay, CA • On-site

$135K - $225K/yr

Full-time

Re-posted 28 days ago

Key responsibilities

  • Partner with product teams to architect, design, and build the foundational infrastructure for the company's products.

  • Design, develop, and deploy highly available and scalable Multi-tenant SaaS solutions on public cloud networks, leveraging technologies such as Kubernetes, Helm, Terraform, and Istio.

  • Collaborate with software development teams to refine CI/CD pipelines, enhance service interfaces, and improve system health through monitoring and observability tools.

Job description

About Ema

Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs.

We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale.

Who you are

We are seeking an experienced DevOps Engineer to join our growing team and play a pivotal role in designing and building our platform and infrastructure as we continue to scale our product and user base. As a part of our team, you will be working in a dynamic, fast-paced environment to ensure the reliability, scalability, and performance of our systems, while focusing on service architecture and deployment, query optimization, distributed systems, data and machine learning infrastructure, and security and authentication. Most importantly, you are excited to be part of a mission-oriented, fast-paced, high-growth startup that can create a lasting impact.

You will:

  1. Partner with product teams to architect, design, and build the foundational infrastructure for our products.

  2. Design, develop, and deploy highly available and scalable Multi-tenant SaaS solutions on any one of the public cloud networks like AWS, Azure and GCP. Leverage technologies such as Kubernetes, Helm, Terraform, and Istio to achieve infrastructure resilience.

  3. Drive the automation of infrastructure tasks, from provisioning to configuration management and deployment, utilizing tools like Terraform, Ansible, and Kubernetes.

  4. Collaborate closely with the software development team to refine CI/CD pipelines, e.g., using GitHub Actions and Cloud Build tools, enhance service interfaces, and improve the overall developer experience.

  5. Architect and implement advanced observability solutions using tools like Prometheus and Grafana. Ensure real-time alerting and error tracking with Sentry and Pagerduty to maintain system health and performance.

  6. Deploy comprehensive testing frameworks, including tools like Selenium for end-to-end testing. Ensure robust integration and system testing to maintain software quality.

  7. Performance Analysis: Regularly monitor system health, analyze performance metrics, and recommend enhancements. This includes optimizing database queries and ensuring peak database performance.

Nice to Have

  1. ML/OPs experience

  2. Experience with Postgres query optimization and related performance improvement techniques.

  3. Experience with event-driven data and machine learning infrastructure, including streaming pipelines, database systems, model training

  4. Experience with air-gapped cloud environments or private clouds

  5. Experience administering complex deployments on Azure, especially AKS

Qualifications:

  • Bachelor's or Master's degree in Computer Science or related field.

  • 3+ years of experience in Infrastructure engineering, or a similar role,

  • Excellent problem-solving skills and the ability to work under pressure in a fast-paced environment.

  • Ability to work independently and as part of a team

  • Experience working with global teams

For California based candidates:
The standard base salary for this position is $135,000-$225,000 annually.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics.