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Machine Learning Ops Engineer Jobs in California

Contract Experience: 10+ years in Software Engineering; 3+ years in AI/ML & Machine Learning Operations Job Overview Our client's Machine Learning AI team is seeking an experienced ML Ops Engineer to ...

ML OPS Engineer Location: Concord, CA ( 5 days a week onsite ) Duration: 12+ Months Contract Job ... ready machine learning platforms across cloud and on-premises environments. The ideal candidate ...

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ML Ops Engineer Concord, CA 12 months contract Job Summary We are seeking an experienced ML Ops Engineer to design, build, and support scalable, secure, and production-ready machine learning ...

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Matterport - Senior ML Ops Engineer

Sunnyvale, CA · On-site

$122K - $168K/yr

Analyze and profile machine learning models to identify performance bottlenecks and areas for optimization. Implement and apply model optimization techniques such as quantization, pruning ...

Sr MLop engineer

San Leandro, CA · On-site

$116K - $159K/yr

Syntricate Technologies is seeking a Sr ML Ops Engineer to drive the full lifecycle of machine learning solutions, bridging the gap between data science model development and production-grade ML Ops ...

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Machine Learning Engineer

San Mateo, CA · On-site

$110K - $165K/yr

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift: N/A Location: San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa ...

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Lead Machine Learning Engineer

San Jose, CA · On-site

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

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Showing results 1-20

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 Sep 10, 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?

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 machine learning ops engineer do?

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 skills and qualifications are needed to be a machine learning ops engineer?

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.

Are machine learning ops engineers in demand?

Machine Learning Ops Engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Kubernetes and TensorFlow. The role is expected to grow as organizations prioritize AI-driven solutions and infrastructure automation.

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 August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $127,083 per year, or $61.1 per hour.

C2C Job Opening - ML Ops Engineer | Concord, CA

Concord, CA • On-site

Other

Posted 22 days ago


Job description

Position: ML Ops Engineer

Type: Contract

Location: Concord, CA (Local candidates only – In-person required)

Job Description

Tachyon Cortex Machine Learning AI team is seeking an experienced ML Ops Engineer to drive the full lifecycle of machine learning solutions.

Key Responsibilities
  • Develop and maintain ML pipelines using MLflow, Kubeflow, or Vertex AI
  • Automate model training, testing, deployment, and monitoring across GCP/AWS/Azure
  • Implement CI/CD workflows for model lifecycle management
  • Monitor model performance and ensure governance compliance
  • Support containerized environments and low-latency model APIs
  • Utilize AutoML tools for rapid deployment and documentation automation
Qualifications
  • 10+ years in Software Engineering & 3+ years in AI/ML Ops
  • Strong skills in Java, Python, SQL, and ML libraries
  • Experience with Docker, Kubernetes, and cloud platforms
  • Familiarity with Airflow, Spark, and ML Ops frameworks
  • Strong DevOps and communication skills
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