Senior Mlops Engineer Jobs in California
Senior Mlops Engineer jobs in California sit at the center of one of the most active machine learning infrastructure markets in the world, concentrated in artificial intelligence, cloud platform engineering, and large-scale model deployment across technology companies, financial services firms, and biotech. Most hiring is in the San Francisco Bay Area, Los Angeles, and San Diego, where employers like Google, Meta, and Qualcomm maintain deep mlops teams. The most in-demand specialties are LLM deployment pipelines, Kubernetes-based model serving, and feature store architecture. Find a role that fits below and apply directly.
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Want to build the data infrastructure that powers autonomous driving at scale? NVIDIA is seeking a Senior MLOps Engineer to join our Autonomous Driving organization in Santa Clara, CA. This individual contributor will design and operate end‑to‑end data and ML pipelines for NVIDIA’s autonomous driving products!
The role builds and operates cloud pipelines that ingest, validate, process, and transform multimodal sensor data from camera, lidar, and radar into training, evaluation, and validation datasets. These pipelines enable NVIDIA’s AV program and customer‑facing autonomy features. Bring ownership, customer focus, and engineering judgment to scale systems and solve problems across teams.
What You Will Be Doing:
Design, build, and operate data pipelines supporting NVIDIA’s autonomous driving technology from levels L2 through L4.
Own architecture, implementation, and operations for cloud pipelines that ingest, process, label, and validate sensor data.
Build observable MLOps systems for model training, ground truth generation, and continuous evaluation at AV scale.
Translate customer and program requirements into production systems with perception, ML, data labeling, infrastructure, and product teams.
Set technical direction, roadmaps, metrics, and operational benchmarks; deliver against program milestones.
Build systems that deliver measurable value to internal and external AV customers.
Contribute through design reviews, implementation, debugging, code reviews, and mentorship.
Work across Python, C++, distributed systems, cloud infrastructure, CI/CD, and data platforms.
What We Need to See:
Bachelor’s or equivalent experience, Master’s, or PhD in Computer Science, Electrical Engineering, or a closely related field (or equivalent experience).
8+ years of engineering experience designing and delivering production distributed systems.
Technical leadership as a senior individual contributor delivering large‑scale systems.
Experience with MLOps, data pipelines, and cloud distributed systems.
Proficiency in Python and C++ for system‑level and performance‑critical implementation.
Experience operating end‑to‑end data or ML pipelines for reliability, scale, and observability.
Prior experience in one or more of the following domains: Autonomous Vehicles, Robotics, Computer Vision, Deep Learning, or GPU‑accelerated computing.
Communication skills that align collaborators and drive execution across functions.
A record of ownership, accountability, and customer‑focused engineering.
Ways to Stand Out from the Crowd:
Experience with AV data platforms handling petabyte‑scale sensor data.
Hands‑on contributions to production MLOps or data infrastructure.
Experience with automotive or robotic systems, including real‑world sensor data pipelines.
Background in distributed cloud systems, workflow orchestration, and large‑scale CI/CD.
Familiarity with 3D geometry, perception pipelines, or data generation based on simulated environments.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Want to build the data infrastructure that powers autonomous driving at scale? NVIDIA is seeking a Senior MLOps Engineer to join our Autonomous Driving organization in Santa Clara, CA. This individual contributor will design and operate end‑to‑end data and ML pipelines for NVIDIA’s autonomous driving products!
The role builds and operates cloud pipelines that ingest, validate, process, and transform multimodal sensor data from camera, lidar, and radar into training, evaluation, and validation datasets. These pipelines enable NVIDIA’s AV program and customer‑facing autonomy features. Bring ownership, customer focus, and engineering judgment to scale systems and solve problems across teams.
What You Will Be Doing:
Design, build, and operate data pipelines supporting NVIDIA’s autonomous driving technology from levels L2 through L4.
Own architecture, implementation, and operations for cloud pipelines that ingest, process, label, and validate sensor data.
Build observable MLOps systems for model training, ground truth generation, and continuous evaluation at AV scale.
Translate customer and program requirements into production systems with perception, ML, data labeling, infrastructure, and product teams.
Set technical direction, roadmaps, metrics, and operational benchmarks; deliver against program milestones.
Build systems that deliver measurable value to internal and external AV customers.
Contribute through design reviews, implementation, debugging, code reviews, and mentorship.
Work across Python, C++, distributed systems, cloud infrastructure, CI/CD, and data platforms.
What We Need to See:
Bachelor’s or equivalent experience, Master’s, or PhD in Computer Science, Electrical Engineering, or a closely related field (or equivalent experience).
8+ years of engineering experience designing and delivering production distributed systems.
Technical leadership as a senior individual contributor delivering large‑scale systems.
Experience with MLOps, data pipelines, and cloud distributed systems.
Proficiency in Python and C++ for system‑level and performance‑critical implementation.
Experience operating end‑to‑end data or ML pipelines for reliability, scale, and observability.
Prior experience in one or more of the following domains: Autonomous Vehicles, Robotics, Computer Vision, Deep Learning, or GPU‑accelerated computing.
Communication skills that align collaborators and drive execution across functions.
A record of ownership, accountability, and customer‑focused engineering.
Ways to Stand Out from the Crowd:
Experience with AV data platforms handling petabyte‑scale sensor data.
Hands‑on contributions to production MLOps or data infrastructure.
Experience with automotive or robotic systems, including real‑world sensor data pipelines.
Background in distributed cloud systems, workflow orchestration, and large‑scale CI/CD.
Familiarity with 3D geometry, perception pipelines, or data generation based on simulated environments.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.See All 6 Senior Mlops Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
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Where California roles are concentrated, by current openings.
Senior Mlops Engineer Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Automotive
What California Employers Look For
The qualifications that appear most often in senior mlops engineer jobs across California.
- Bachelor's or master's degree in computer science, data engineering, or a related technical field
- Five or more years of mlops or machine learning infrastructure engineering experience required
- Hands-on proficiency with Kubernetes, Kubeflow, MLflow, or comparable orchestration and experiment-tracking platforms
- Experience building and maintaining CI/CD pipelines for model training, validation, and production deployment
- Demonstrated ability to design scalable feature stores, model registries, and monitoring systems in cloud environments
- Strong programming skills in Python plus familiarity with distributed computing frameworks such as Spark or Ray
Senior Mlops Engineer Jobs in California: Frequently Asked Questions
How do you become a senior mlops engineer in California?
Senior mlops engineer roles in California require a bachelor's degree in computer science, data engineering, or a closely related field, though many hiring managers at California technology companies prioritize a strong portfolio of deployed machine learning systems over credentials alone. There is no state-issued license for this role. Candidates typically advance by building production mlops experience at a California-based technology, biotech, or fintech employer, then demonstrating ownership of model serving infrastructure, monitoring pipelines, and platform reliability at scale.
How much do senior mlops engineers make in California?
Senior mlops engineers in California earn a median of about $134,440 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $58,340 for the lowest 10% to over $222,690 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire senior mlops engineers in California?
Employers hiring senior mlops engineers in California right now include Grindr, Bosch, and NVIDIA, based on current listings on Migrate Mate as of August 2026. California's concentration of AI-first technology companies and cloud platform divisions means demand is distributed across both large hyperscalers and well-funded mid-stage startups headquartered in the Bay Area and Los Angeles.
Which California cities have the most senior mlops engineer jobs?
The cities with the most senior mlops engineer openings in California are Sunnyvale, Ontario, and Palo Alto. The Bay Area leads because of its density of AI research labs, cloud infrastructure teams, and enterprise software headquarters, while Los Angeles and San Diego draw from their growing biotech, entertainment technology, and defense technology sectors, which have increasingly built in-house machine learning operations functions.
Are there remote senior mlops engineer jobs in California?
Yes, and more than most engineering fields, since mlops work is centered on cloud platforms and CI/CD tooling that require no physical presence. About 75% of senior mlops engineer openings tied to California are remote or hybrid as of August 2026, reflecting the infrastructure-heavy nature of the role. Model monitoring, pipeline automation, and platform engineering tasks are the most consistently remote, while hands-on GPU cluster management or on-site data center work tends to require in-person presence.
How can I get hired as a senior mlops engineer in California with little or no experience?
The most realistic entry path is through a data engineering or machine learning engineering role at a California technology company, then building toward mlops ownership incrementally. Large California employers like Apple, Nvidia, and Salesforce post associate-level machine learning infrastructure and platform engineering positions that serve as direct pipelines into senior mlops work. Candidates who complete a portfolio project demonstrating end-to-end model deployment on a public cloud platform, particularly on Google Cloud or AWS where California hiring concentrates, consistently stand out over applicants with coursework alone.
Where can I find and apply to senior mlops engineer jobs in California?
You can find and apply to senior mlops engineer jobs in California on Migrate Mate, which lists current California openings from employers actively hiring for this role. Search the listings to find roles that match your experience and target location, then apply directly to the ones that fit.
See All 6 Senior Mlops Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
Find Senior Mlops Engineer Jobs