ZipRecruiter

Log In

1

Senior Machine Learning Ops Engineer Jobs in Los Angeles, CA

Yum! Brands

Sr Machine Learning Engineer

Irvine, CA

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

Yum

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

Yum Brands

Sr Machine Learning Engineer

Irvine, CA

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

Warnerbros

Senior Machine Learning Engineer

Burbank, CA · On-site

$111K - $153K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do Warner Bros. Discovery (WBD) is home to the world's most iconic entertainment, news, and sports ...

next page

Showing results 1-20

All JobsMachine Learning Ops Engineer JobsSenior Machine Learning Ops Engineer JobsSenior Machine Learning Ops Engineer Jobs in Los Angeles, CA

Senior Machine Learning Ops Engineer information

See Los Angeles, CA salary details

$64.1K

$136.4K

$197.7K

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

As of Aug 30, 2026, the average yearly pay for senior machine learning ops engineer in Los Angeles, CA is $136,366.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,600.00 and $154,600.00 per year, depending on experience, location, and employer.

What is a senior machine learning ops engineer?

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 are the key skills and qualifications needed to thrive as a senior machine learning ops engineer?

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 the most commonly searched types of Machine Learning Ops Engineer jobs in Los Angeles, CA?

The most popular types of Machine Learning Ops Engineer jobs in Los Angeles, CA are:

What are popular job titles related to Senior Machine Learning Ops Engineer jobs in Los Angeles, CA?

For Senior Machine Learning Ops Engineer jobs in Los Angeles, CA, the most frequently searched job titles are:

What job categories do people searching Senior Machine Learning Ops Engineer jobs in Los Angeles, CA look for?

The top searched job categories for Senior Machine Learning Ops Engineer jobs in Los Angeles, CA are:

Senior Machine Learning Ops Engineer jobs near you
Infographic showing various Senior Machine Learning Ops Engineer job openings in Los Angeles, CA as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 21% Part Time, and 1% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $136,366 per year, or $65.6 per hour.

Senior Machine Learning Engineer - Hybrid schedule

Calance US

Los Angeles, CA • Hybrid

$112K - $154K/yr

Full-time

Medical, Dental, Vision, Life

Posted 4 days ago

Job description

We are hiring Senior Machine Learning Engineer - Hybrid schedule for a Full Time position in Los Angeles or NYC, CA
Sr. Machine Learning Engineer
About the Role
The Senior Machine Learning Engineer is an integral part of the Technology & Information Services team. This role will be responsible for the design, deployment, and optimization of custom workflows using classical machine learning (ML), Natural Language Processing (NLP), and Generative AI techniques to enhance legal and business processes, while designing, building, and optimizing custom machine learning models and workflows to optimize legal and business workflows. This role will be located in our Global Services Office. Please note that this role may be eligible for a flexible working schedule that allows for a hybrid and in-office presence.
Responsibilities & Qualifications
Other key responsibilities include:
Contributing to the entire lifecycle of AI/ML applications including concept, design, test, release, and support
Developing and maintaining robust ML pipelines for training, validation, and model deployment
Working with DevOps or infrastructure teams to manage GPU resources, model serving frameworks, and CI/CD workflows
Evaluating and integrating new research, tools, and frameworks to advance the team s capabilities
Developing ML/GenAI solutions in a professional manner, and in accordance with established deliverable schedules and firm procedures
Protecting and maintaining any highly sensitive, confidential, privileged, financial, and/or proprietary information that retains
We d love to hear from you if you:
Demonstrate proficiency with Python including experience with libraries and frameworks relevant to GenAI application development (e.g., LangChain)
Exhibit proficiency with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn), and serving tools (e.g., TorchServe, ONNX, Triton)
Display proficiency in training or fine-tuning language models (e.g., BERT, Llama2, GPT), and their optimization (LoRA, knowledge distillation, pruning, and quantization)
And have:
A bachelor s degree and master s degree in information systems, computer science, engineering, data science, or a related field, preferably
A minimum of five (5) years of experience in industry roles focused on machine learning, applied AI, or data science
A minimum of five (5) years of Python industry experience
A minimum of three (3) years of experience working with agile teams
Experience building and productizing ML models and systems
Estimated Pay Range: 175-195K

Apply