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Senior Machine Learning Ops Engineer Jobs in Novato, CA

EvenUp

Senior Machine Learning Engineer

San Francisco, CA · Remote

$196K - $265K/yr

Senior Machine Learning Engineer At EvenUp, we leverage cutting-edge AI to bring fairness and ... ops- team@evenuplaw.com. Examples of fraudulent domains include "careers-evenuplaw.com" and ...

Freenome

Senior Machine Learning Engineer

Brisbane, CA · On-site

$147K - $194K/yr

The Senior Machine Learning Research Engineer will primarily be responsible for developing and deploying the infrastructure needed to support development of such DL models: enabling distributed DL ...

Freenome

Senior Machine Learning Engineer

Brisbane, CA · On-site +1

$147K - $194K/yr

The Senior Machine Learning Research Engineer will primarily be responsible for developing and deploying the infrastructure needed to support development of such DL models: enabling distributed DL ...

Kikoff

Senior Machine Learning Engineer

San Francisco, CA

$123K - $169K/yr

We are seeking a Senior Machine Learning Engineer to join our team. This role will focus on developing and maintaining machine learning infrastructure and operations, particularly for our cash ...

Kikoff

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

We are seeking a Senior Machine Learning Engineer to join our team. This role will focus on developing and maintaining machine learning infrastructure and operations, particularly for our cash ...

Hum AI

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Senior Machine Learning Engineer Location: San Francisco About Hum.ai Hum.ai is building planetary superintelligence. Backed by top funds, we've raised $10M+ and are now heads down building. Join us ...

Hive

Senior Machine Learning Engineer

San Francisco, CA · On-site

$160K - $250K/yr

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

Hive

Senior Machine Learning Engineer

San Francisco, CA · On-site

$160K - $250K/yr

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

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All JobsMachine Learning Ops Engineer JobsSenior Machine Learning Ops Engineer JobsSenior Machine Learning Ops Engineer Jobs in Novato, CA

Senior Machine Learning Ops Engineer information

See Novato, CA salary details

$69.9K

$148.6K

$215.4K

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

As of Aug 1, 2026, the average yearly pay for senior machine learning ops engineer in Novato, CA is $148,586.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,700.00 and $168,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Senior Machine Learning Ops Engineer, you need expertise in machine learning, software engineering, cloud platforms, and experience with CI/CD pipelines, often supported by a computer science degree or equivalent experience. Proficiency with tools like Docker, Kubernetes, TensorFlow, PyTorch, and cloud services such as AWS, GCP, or Azure is typically required, along with familiarity with MLOps frameworks. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and manage complex ML model deployments. These skills are essential to ensure reliable, scalable, and efficient deployment of machine learning models in production environments.

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

Senior Machine Learning Ops Engineers often encounter challenges such as ensuring model reproducibility, managing model versioning, and automating deployment pipelines for scalability. Another key challenge is monitoring model performance and data drift in production, which requires robust logging and alerting systems. Collaborating closely with data scientists, software engineers, and IT teams is essential to address these challenges and maintain a stable, efficient ML infrastructure.

What is the difference between Senior Machine Learning Ops Engineer vs Data Engineer?

AspectSenior Machine Learning Ops EngineerData Engineer
CredentialsExperience with ML frameworks, cloud platforms, scripting, and DevOps toolsStrong SQL, ETL, database, and programming skills, often with cloud experience
Work EnvironmentFocus on deploying, monitoring, and maintaining ML models in productionDesigning and building data pipelines and infrastructure for data processing
Industry UsageCommon in AI/ML-focused companies, tech firms, and data-driven organizationsWidespread across industries for data management and analytics

While both roles involve working with data and cloud platforms, the Senior Machine Learning Ops Engineer specializes in deploying and maintaining machine learning models, whereas the Data Engineer focuses on building data pipelines and infrastructure. Understanding these distinctions helps in choosing the right career path or job search focus.

What are Senior Machine Learning Ops Engineers?

Senior Machine Learning Ops (MLOps) Engineers are experienced professionals who design, build, and maintain the infrastructure and tools needed to deploy, monitor, and scale machine learning models in production environments. They work at the intersection of data science, software engineering, and DevOps to ensure ML models are robust, reliable, and secure. Their responsibilities often include automating model training pipelines, managing cloud resources, implementing CI/CD for ML, and ensuring model reproducibility. Senior MLOps Engineers also mentor junior staff and help define best practices for the organization’s ML workflow.
What cities near Novato, CA are hiring for Senior Machine Learning Ops Engineer jobs? Cities near Novato, CA with the most Senior Machine Learning Ops Engineer job openings:
Senior Machine Learning Ops Engineer jobs near you

Sr. Machine Learning Ops Engineer

Hayden AI

San Francisco, CA • On-site

$200K - $260K/yr

Full-time

Re-posted 3 days ago

Job description

About Us
At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.
From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.
About the role:
As a Senior MLOps Engineer within the Perception Deep Learning team, you will lead the design and evolution of our machine learning platform, enabling teams to build, deploy, and scale intelligent systems with reliability and speed. In this role, you will partner closely with perception, deep learning and platform engineers to build infrastructure to train and operationalize machine learning models and drive best practices across the ML lifecycle.
You will play a key role in shaping the architecture of our ML infrastructure, from data ingestion and training pipelines to deployment, monitoring, and governance. As a senior member of the team, you will influence technical strategy, mentor engineers, and champion a culture of reproducibility, observability, and continuous improvement.
Key responsibilities:
  • Architect, design, deploy, and operate scalable cloud-based MLOps platforms and workflows that enable efficient training, evaluation, deployment, monitoring, and lifecycle management of AI/ML models.
  • Own the technical strategy and evolution of ML infrastructure, identifying architectural bottlenecks and driving cross-functional initiatives to improve developer productivity, experimentation velocity, scalability, and operational efficiency.
  • Build robust, reliable, and automated systems that enable teams to ship new models and features rapidly while maintaining high standards for quality, reproducibility, observability, security, and production reliability.
  • Define and implement infrastructure optimization strategies that balance performance, scalability, reliability, and cost across cloud and compute resources.
  • Evaluate emerging tools, technologies, and industry best practices in MLOps, cloud infrastructure, and ML systems, and lead their adoption where they can meaningfully improve ML development and production workflows.
  • Establish engineering best practices for ML infrastructure, including system design, code quality, testing, CI/CD, monitoring, documentation, and operational readiness.
  • Provide technical leadership and mentorship to engineers, lead design and code reviews, and help raise the engineering quality and technical capabilities of the broader team.
  • Partner closely with ML engineers, researchers, data engineers, and product teams to translate evolving AI/ML requirements into scalable and maintainable infrastructure solutions.
  • Drive complex, ambiguous infrastructure projects from technical strategy and architecture through implementation, production deployment, and long-term operational ownership.

Key Qualifications:
  • A Bachelors Degree or a Masters Degree in Computer Science, Electrical Engineering, or a related field.
  • Core Skills: General Software Engineering skills with 6+ years of programming experience in python and the surrounding tooling ecosystem along with familiarity in linux and expertise in infrastructure, cloud and/or MLOps,.
  • Personal Attributes: Team player, good communication skills, self starter.
  • Strong teamwork and communication skills to collaborate with cross-functional teams, including ML and software engineers.
  • Nice to Have: Experience building MLOps pipelines for deep learning based perception solutions on AWS or GCP

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