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Machine Learning Ops Engineer Jobs in California

Machine Learning Engineer LeanData helps the world's fastest-growing companies automate, simplify, and accelerate revenue. We are looking for a curious and innovative Machine Learning Engineer to ...

As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive meaningful business outcomes at scale. You will work cross-functionally to bring innovative machine ...

Machine Learning Engineer

San Jose, CA · On-site

$125K - $234K/yr

Implement ML-Ops best practices to ensure scalable, reliable, and efficient machine learning ... Proficiency in one or more programming languages such as Python, Scala, Java, or SQL. * Proficiency ...

Machine Learning Engineer Machina Labs is changing the way manufacturing works. We build intelligent, software-defined factories that produce complex metal structures directly from digital design. By ...

Dev Ops Engineer

San Francisco, CA · On-site

$62.25 - $85/hr

Its proprietary technology combines robotics, machine learning, and advanced computer vision to ... We are looking to hire a Dev Ops Engineer for our Software Team. What You'll Do: * Own the ...

... engineers across Apple.","responsibilities":"Design, train and tune machine learning algorithms, support camera architects to drive innovative solutions for imaging and sensing challenges, and ...

Machine Learning Engineer San Mateo, Pittsburgh Company Overview At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios ...

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only h1 candidate About the Role: Our direct client is hiring a Machine Learning Engineer for their ...

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Machine Learning Ops Engineer information

See California salary details

$31.1K

$127.1K

$191K

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

As of Jun 19, 2026, the average yearly pay for machine learning ops engineer in California is $127,083.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,200.00 and $153,000.00 per year, depending on experience, location, and employer.

What is a Machine Learning Ops Engineer job?

A Machine Learning Ops Engineer (MLOps Engineer) focuses on deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and software engineering, ensuring models run efficiently, reliably, and at scale. Their responsibilities include automating workflows, managing infrastructure, and ensuring CI/CD pipelines for ML models. They work with tools like Kubernetes, Docker, and cloud platforms to streamline model deployment. Ultimately, an MLOps Engineer ensures that machine learning models are operationalized and continuously improved in a real-world environment.

What does a typical day look like for a Machine Learning Ops Engineer?

A typical day for a Machine Learning Ops Engineer involves collaborating with data scientists to streamline the deployment of models, building and maintaining scalable infrastructure on cloud services, and automating workflows with CI/CD tools. You may troubleshoot issues in production environments, monitor model performance, and implement solutions for model versioning and retraining. Often, you’ll work closely with software engineers, DevOps teams, and data analysts to ensure seamless integration of machine learning solutions into products. This cross-functional role keeps you engaged with cutting-edge technology and provides opportunities to influence both technical and business outcomes.

What are the key skills and qualifications needed to thrive in the Machine Learning Ops Engineer position, and why are they important?

To thrive as a Machine Learning Ops Engineer, you need a solid grasp of machine learning concepts, cloud platforms, software engineering, and DevOps practices, typically supported by a degree in computer science or a related field. Experience with tools like Docker, Kubernetes, TensorFlow, CI/CD pipelines, and certifications such as AWS Certified Machine Learning – Specialty are highly valuable. Strong problem-solving skills, communication, and the ability to work collaboratively across data science and engineering teams set top candidates apart. These skills ensure reliable deployment, scalability, and optimization of machine learning models in production environments.

What cities in California are hiring for Machine Learning Ops Engineer jobs? Cities in California with the most Machine Learning Ops Engineer job openings:
Infographic showing various Machine Learning Ops Engineer job openings in California as of June 2026, with employment types broken down into 6% Internship, 88% Full Time, 3% Contract, and 3% Nights. Highlights an 91% In-person, and 9% Remote job distribution, with an average salary of $127,083 per year, or $61.1 per hour.
Machine Learning Engineer

Machine Learning Engineer

LeanData

Santa Clara, CA • On-site

Other

Retirement, PTO

Posted 7 days ago


Job description

Machine Learning Engineer

LeanData helps the world's fastest-growing companies automate, simplify, and accelerate revenue.

We are looking for a curious and innovative Machine Learning Engineer to explore, experiment and build AI driven solutions that analyze customer journey and go to market data. The ideal candidate will have a passion for experimenting with various AI libraries and tools, making recommendations, and collaborating with cross-functional teams to develop a product that uncovers insights tied to our customers' success.

Role

This role is based at our Santa Clara, CA office. An ML Engineer is required to be in office Mondays and Wednesdays each week. Lunch will be provided on those days.

What You'll Be Doing
  • Research, prototype and experiment with a variety of AI/ML libraries, frameworks, and tools to identify the best approaches for analyzing go to market data
  • Analyze findings from experiments and provide clear, actionable recommendations on optimal AI/ML methodologies and technologies
  • Collaborate with product and engineering teams to design, develop and deploy a scalable AI-powered product that delivers insights into a go-to-market strategies and their impact on success
  • Build, evaluate, and optimize machine learning models to ensure high performance, accuracy, and scalability
  • Stay updated on emerging AI/ML trends, tools, and techniques that can be used incorporated into the product
Requirements
  • Strong ability to experiment with and explore diverse AI/ML libraries and tools
  • 6+ years of experience in machine learning with hands on experience building and deploying ML models
  • Comfortable working with Python or similar programming languages for data analysis and model development.
  • Ability to analyze complex datasets, identify patterns, and translate findings into business-relevant insights.
  • Experience leading and mentoring a team of junior engineers while providing technical guidance and fostering a collaborative environment.
  • Collaborative mindset with experience working in cross-functional teams.
  • Master's degree in Machine Learning or Computer Science (heavily focused on Machine Learning/Artificial Intelligence)
  • Desire to learn
  • Experience building and maintaining robust data and machine learning pipelines, including preprocessing, model training, and deployment workflows.
Bonus Points If You Have
  • Familiarity with natural language processing (NLP)
  • Prior experience contributing to the development of a customer-facing AI product
  • Familiarity with data processing tools and AWS is a plus.
  • Excellent verbal and written communication skills to present findings and recommendations to technical and non-technical stakeholders.
Why Work At LeanData
  • LeanData covers employee insurance premiums up to 90%
  • Stock options in LeanData for all full-time employees
  • Flexible PTO
  • 401K plan