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Mlops Engineer Jobs in San Ramon, CA (NOW HIRING)

Atomic Machines

MLOps Engineer

Emeryville, CA

We are seeking an MLOps Engineer to join our AI and Modeling & Simulation org within the Data Engineering and Analytics team. You will build and operate the infrastructure that takes AI and machine ...

Atomic Machines

MLOps Engineer

Emeryville, CA · On-site

We are seeking an MLOps Engineer to join our AI and Modeling & Simulation org within the Data Engineering and Analytics team. You will build and operate the infrastructure that takes AI and machine ...

4i Americas

MLOPs Engineer

Concord, CA · On-site

Ensure best practices in scalability, security, and reliability Required Skills & Qualifications * 2-5 years of experience in MLOps, DevOps, or ML Engineering * Strong proficiency in Python * Hands ...

Atomic Machines

MLOps Engineer

Emeryville, CA · On-site

We are seeking an MLOps Engineer to join our AI and Modeling & Simulation org within the Data Engineering and Analytics team. You will build and operate the infrastructure that takes AI and machine ...

Hirekeyz Inc

MLOps Engineer

San Francisco, CA · On-site

Role: MLOps Engineer Location: San Francisco, California Duration: Long Term Contract Key Responsibilities * Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI.

Tror AI for everyone

MLOPS Engineer

Concord, CA · On-site

Job Role: MLOPS Engineer Job Location: Concord, CA (100% Onsite) Job Type: Contract Key Responsibilities: * Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI.

Nace AI

Senior MLOps Engineer

Palo Alto, CA · On-site

$122K - $168K/yr

As a Senior MLOps Engineer, you will own the infrastructure that takes Nace.AI's models from research to reliable, production-grade systems. Our infrastructure generates task-specific Small Language ...

CYNET SYSTEMS

Senior​ AI/MLOPS Engineer

Pleasanton, CA · On-site

$75 - $80/hr

Pay Range: $75hr - $80hr Requirement/Must Have: * 10+ years of experience in AI and MLOps. * Strong Python programming skills. * Experience with machine learning frameworks (TensorFlow, PyTorch ...

Zeitview

Senior MLOps Engineer I

San Francisco, CA · On-site

$123K - $169K/yr

As the Senior MLOps Engineer I, you will help turn the models built by our ML Scientists, Data Scientists, and Perception Engineers into reliable, production-grade services. You'll work on the ...

Zeitview

Senior MLOps Engineer I

San Francisco, CA · On-site +1

$123K - $169K/yr

As the Senior MLOps Engineer I, you will help turn the models built by our ML Scientists, Data Scientists, and Perception Engineers into reliable, production-grade services. You'll work on the ...

Intuitive

Sr MLOps Engineer

Sunnyvale, CA

$122K - $168K/yr

... DevOps, or MLOps roles, or equivalent practical experience * Demonstrated experience operating Kubernetes in production (networking, storage, RBAC, troubleshooting) * Strong scripting/automation ...

Intuitive Surgical

Sr MLOps Engineer

Sunnyvale, CA · On-site

$122K - $168K/yr

... DevOps, or MLOps roles, or equivalent practical experience * Demonstrated experience operating Kubernetes in production (networking, storage, RBAC, troubleshooting) * Strong scripting/automation ...

Intuitive

Sr MLOps Engineer

Sunnyvale, CA · On-site

$122K - $168K/yr

... DevOps, or MLOps roles, or equivalent practical experience * Demonstrated experience operating Kubernetes in production (networking, storage, RBAC, troubleshooting) * Strong scripting/automation ...

Stanford Health Care

DevOps Engineer

Newark, CA · On-site

$59.25 - $81.25/hr

A Brief Overview The MLOPs Engineer will play an integral role incorporating Artificial Intelligence (AI) within Stanford Health Care. The solutions will impact patient care, medical research, and ...

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All JobsMlops Engineer JobsMlops Engineer Jobs in San Ramon, CA

Mlops Engineer information

What is an MLOps engineer?

An MLOps Engineer is responsible for deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and operations by automating workflows, optimizing infrastructure, and ensuring model reliability. Their role includes CI/CD for ML models, data pipeline management, and performance monitoring. They also work with cloud platforms, containerization, and orchestration tools to scale ML systems efficiently.

What are some common challenges MLOps engineers face in their daily work?

Mlops Engineers often encounter challenges in integrating new machine learning models into existing production systems while ensuring minimal downtime and maintaining data integrity. Managing the scaling and orchestration of models across various cloud or on-prem environments can be complex, requiring close coordination with data scientists and DevOps teams. Staying up to date with rapidly evolving tools and best practices is also essential in this field. Addressing these challenges provides valuable opportunities to innovate and improve both technical processes and team collaboration.

What are the key skills and qualifications needed to thrive as an MLOps engineer, and why are they important?

To thrive as an Mlops Engineer, you need strong skills in software engineering, machine learning pipelines, and cloud infrastructure, often backed by a degree in computer science, engineering, or a related field. Familiarity with tools such as Docker, Kubernetes, TensorFlow, AWS/GCP/Azure, and CI/CD systems is essential, and certifications like AWS Certified Machine Learning or Kubernetes Administrator are often valued. Effective communication, problem-solving, and teamwork are crucial soft skills for collaborating across data science and IT teams. These abilities enable Mlops Engineers to efficiently deploy, manage, and scale machine learning models in dynamic production environments.

What do you need to be a MLOps engineer?

To become a MLOps engineer, you typically need a strong background in software engineering, machine learning, and cloud platforms. Proficiency in programming languages like Python, experience with containerization tools such as Docker, and knowledge of CI/CD pipelines are essential. Certifications in cloud services and familiarity with tools like Kubernetes and ML frameworks also enhance qualifications.

Who earns more, ML engineer or MLOps engineer?

MLOps engineers typically earn slightly more than ML engineers due to their focus on deploying, maintaining, and scaling machine learning systems, which requires expertise in cloud platforms, automation, and infrastructure. Salary differences can vary based on experience, location, and company size, but MLOps roles often command higher compensation because of their specialized skill set.

What are popular job titles related to Mlops Engineer jobs in San Ramon, CA?

For Mlops Engineer jobs in San Ramon, CA, the most frequently searched job titles are:

What job categories do people searching Mlops Engineer jobs in San Ramon, CA look for?

The top searched job categories for Mlops Engineer jobs in San Ramon, CA are:

What cities near San Ramon, CA are hiring for Mlops Engineer jobs?

Cities near San Ramon, CA with the most Mlops Engineer job openings:

Mlops Engineer jobs near you
Infographic showing various Mlops Engineer job openings in San Ramon, CA as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.

MLOps Engineer

Emeryville, CA

Atomic Machines
Computer and Electronic Product Manufacturing • 1 - 10 employees
Learn more about Atomic Machinesexternal

Full-time

Posted 4 days ago

Job description

Atomic Machines is ushering in a new era of micromanufacturing with its Matter Compiler™ technology platform. This platform enables new classes of micromachines to be designed and built by providing manufacturing processes and a materials library that are inaccessible to semiconductor manufacturing methods. It unlocks MEMS manufacturing not only for device classes that could never be produced by semiconductor methods, but also for entirely new categories. Furthermore, this digital platform is fully programmable in the way 3D printing is digital—but whereas 3D printing produces parts of a single material using a single process, the Matter Compiler™ technology platform is a multi-process, multi-material system: bits and raw materials go in, and complete, functional micromachines come out. The Atomic Machines team has also created an exciting first device—made possible only through the Matter Compiler™ technology platform—that we will be unveiling to the world soon.
 
Our offices are in Emeryville and Santa Clara, California.
About The Role:

We are seeking an MLOps Engineer to join our AI and Modeling & Simulation org within the Data Engineering and Analytics team.

You will build and operate the infrastructure that takes AI and machine learning models from experimentation to reliable production - covering training, deployment, serving, monitoring, and continuous improvement. This is a DevOps-leaning MLOps role centered on the model feedback loop: connecting production signals and expert feedback back to training so models improve as the system operates.

We are looking for senior-level candidates who can take meaningful ownership of production ML infrastructure. The scope and seniority of the role will be shaped by the candidate's experience, technical depth, and demonstrated impact.

You will work closely with Data, AI, Process, Design, and Software engineers in a highly cross-functional environment.

What You'll Do:
  • Build and evolve the MLOps platform and CI/CD: Own the path from experiment to production, including experiment tracking, model registry, packaging, automated training and retraining, deployment, and safe rollout and rollback.
  • Operate model serving infrastructure: Build reliable, scalable batch, streaming, and real-time inference for models and digital twins supporting design, process control, scheduling, and inspection.
  • Build ML data and feature pipelines: Turn machine telemetry, process and knowledge graphs, images, time-series, agentic conversations, and other production data into contextualized, model-ready datasets and features.
  • Maintain ML data infrastructure: Support feature-store capabilities and a lakehouse foundation using Apache Iceberg on S3, with strong data quality, lineage, versioning, and reproducibility.
  • Close the model feedback loop: Build model observability and human-in-the-loop systems that capture production signals and expert corrections, version them as ground truth, and feed them into evaluation and retraining workflows.
  • Create paved roads for ML development: Develop standardized tooling and workflows that enable Data and AI engineers to move quickly while maintaining production reliability and reproducibility.
  • Drive technical ownership: Identify infrastructure, reliability, and scalability challenges and drive solutions from design through production. More senior candidates will have opportunities to shape architecture, technical direction, and engineering practices across the ML platform.
  • Collaborate across disciplines: Work with Process, Chemical, Materials, Simulation, Software, Data, and AI engineers to define deployment, serving, and data-collection requirements.
What You'll Need:
  • 5+ years of relevant industry experience building production software, infrastructure, data, or machine learning systems. We value demonstrated technical depth, ownership, and impact over a specific number of years.
  • Proven experience building and operating machine learning systems in production, with a strong MLOps/DevOps orientation.
  • Strong DevOps fundamentals, including CI/CD, containers, Kubernetes, cloud infrastructure, and infrastructure-as-code.
  • Proficiency in Python and SQL.
  • Hands-on experience with MLflow or similar tooling for experiment tracking, model registry, and model lifecycle management.
  • Experience with S3, lakehouse technologies such as Apache Iceberg, and workflow orchestration tools such as Airflow or Dagster.
  • Experience building pipelines for multimodal ML data, including images, time-series, structured, and semi-structured data.
  • Familiarity with manufacturing systems, sensors, process automation, or other physical-world data systems.
  • Strong problem-solving skills, attention to data quality and reliability, and clear technical communication.
  • Bachelor's or Master's degree in Computer Science, Data Engineering, Data Science, or a related STEM field, or equivalent practical experience.
  • This role is open across multiple levels, from early in career though Staff (L4 through L6). We'll determine the appropriate level and compensation based on your experience, skills, and the scope of the role through the interview process.
Bonus Points For:
  • Experience with feature stores, human-in-the-loop systems, active learning, or data-labeling infrastructure.
  • Robotics or robotic automation experience, including sensors, vision systems, or robotics data.
  • Experience operating ML systems in manufacturing or other physical-world environments.
  • Experience building internal tools for expert feedback, labeling, model evaluation, or model interaction.
  • Experience designing shared ML infrastructure or platforms used across multiple teams or applications.

The compensation for this position also includes equity and benefits.

Salary Range
$200,000—$250,000 USD

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