ZipRecruiter

Log In

1

Mlops Jobs in Riverside, CA (NOW HIRING)

Kia America

Data Scientist- Applied AI

Irvine, CA · On-site

Partner with IT system developers on model deployment and MLOps best practices to ensure production readiness 4th Priority - 20% Clear documentation, source code management, and reproducible analysis

Yum Brands

Sr Machine Learning Engineer

Irvine, CA

$112K - $154K/yr

The ideal candidate combines strong software engineering and MLOps fundamentals with a passion for building reliable, scalable machine learning systems. Required Qualifications * Bachelor's or Master ...

Kia America

Data Scientist- Applied AI

Irvine, CA · On-site +1

Partner with IT system developers on model deployment and MLOps best practices to ensure production readiness 4th Priority - 20% Clear documentation, source code management, and reproducible analysis

Cotality

Director, ML Engineering

Irvine, CA · On-site

MLOps Excellence: Drive the adoption of CI/CD for ML (CT - Continuous Training), ensuring robust model versioning, automated testing, and seamless deployment via Vertex AI or GKE. * Data Strategy ...

Diality Inc

Cloud & Digital Platform Architect

Irvine, CA · On-site

$177K - $196K/yr

Build and operationalize MLOps pipelines. * Leverage AI-assisted tools (e.g. Codex, Claude, GitHub Copilot) to: * Accelerate development * Improve code quality * Automate documentation and testing

PDS Health

Sr Engineer, AI Solutions

Irvine, CA · On-site

$130K - $168K/yr

Deploy and manage AI models using containerization, orchestration and Machine Learning Operations (MLOps) best practices (Continuous Integration and Deployment (CI/CD) pipelines on AWS and/or GCP)

PDS Health

Sr Engineer, AI Solutions

Irvine, CA · On-site

$130K/yr

Deploy and manage AI models using containerization, orchestration and Machine Learning Operations (MLOps) best practices (Continuous Integration and Deployment (CI/CD) pipelines on AWS and/or GCP)

ISite Technologies Inc

Senior AI Engineer

Irvine, CA

$112K - $154K/yr

API contracts and versioning Reliability (retry logic, circuit breakers, idempotency) Enable reusability of platform capabilities across teams and applications 4. Deployment, MLOps & Operational ...

New

Qcells

Applied AI Engineer

Irvine, CA · On-site

$160K - $190K/yr

Familiarity with MLOps and DevOps practices as applied to AI/ML model lifecycle management, deployment, and monitoring. * Experience working with SQL and NoSQL databases and performing data ...

Qcells

Applied AI Engineer

Irvine, CA

$160K - $190K/yr

Familiarity with MLOps and DevOps practices as applied to AI/ML model lifecycle management, deployment, and monitoring. * Experience working with SQL and NoSQL databases and performing data ...

Yum

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

The ideal candidate combines strong software engineering and MLOps fundamentals with a passion for building reliable, scalable machine learning systems. Responsibilities * Support the deployment ...

Cotality

Senior Data Governance Professional

Irvine, CA · On-site

$72.25 - $96.50/hr

Roll out and integrate governance processes with enterprise workflows, including MLOps, DataOps, PMO, and agile software development life cycles. * Establish robust change management processes to ...

Yum! Brands

Sr Machine Learning Engineer

Irvine, CA

$112K - $154K/yr

The ideal candidate combines strong software engineering and MLOps fundamentals with a passion for building reliable, scalable machine learning systems. Responsibilities * Support the deployment ...

FieldAI

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$112K - $154K/yr

Maintain MLOps workflows for versioning, experiment tracking, reproducibility, and CI/CD. * Ensure reliability and observability with monitoring, logging, and alerting. * Collaborate with AI/ML ...

next page

Showing results 1-20

All JobsMlops JobsMlops Jobs in Riverside, CA

Mlops information

See Riverside, CA salary details

$102.4K

$160.7K

$191.2K

How much do mlops jobs pay per year?

As of Jun 11, 2026, the average yearly pay for mlops in Riverside, CA is $160,741.00, according to ZipRecruiter salary data. Most workers in this role earn between $151,874.00 and $174,579.00 per year, depending on experience, location, and employer.

What is the difference between Mlops vs Data Engineer?

AspectMlopsData Engineer
Primary FocusDeploying, managing, and monitoring machine learning models in productionBuilding and maintaining data pipelines and infrastructure for data processing
Skills & CertificationsMachine learning, DevOps, cloud platforms, scriptingSQL, ETL, data warehousing, programming
Work EnvironmentCollaborates with data scientists, software engineers, and DevOps teamsWorks with data analysts, data scientists, and software developers
Industry UsageAI/ML projects, production environments, cloud servicesData infrastructure, analytics, big data processing

While both Mlops and Data Engineers work closely with data and cloud technologies, Mlops specialists focus on deploying and maintaining machine learning models in production, ensuring their scalability and reliability. Data Engineers primarily build data pipelines and infrastructure to support data analysis and ML workflows. Understanding these distinctions helps organizations assign the right roles for their AI and data projects.

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 a strong background in machine learning, software engineering, and DevOps principles, often supported by a degree in computer science or a related field. Proficiency with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (e.g., AWS, Azure, GCP), and ML frameworks is typically required, along with certifications in cloud or DevOps technologies. Strong problem-solving skills, collaboration, and communication abilities help MLOps professionals excel in cross-functional teams and manage complex workflows. These skills are vital for reliably deploying, monitoring, and scaling machine learning models in production environments, ensuring efficiency and robustness.

Is MLOps a good career path?

MLOps is a growing field that combines machine learning, software engineering, and operations to deploy and maintain AI models efficiently. It offers high demand for skills in cloud platforms, automation, and data management, making it a promising career choice for those interested in AI infrastructure. Professionals in MLOps often work with tools like Docker, Kubernetes, and CI/CD pipelines, and typically require a strong understanding of both machine learning and software development.

What are some common challenges faced by MLOps professionals when deploying machine learning models to production?

MLOps professionals often encounter challenges such as ensuring reproducibility of models, managing version control for both code and data, and maintaining model performance over time. Handling continuous integration and deployment (CI/CD) pipelines for ML models can be complex, especially when dealing with large datasets and evolving algorithms. Additionally, coordinating with data scientists, software engineers, and DevOps teams to streamline workflows and monitor models post-deployment are key responsibilities that require both technical expertise and strong collaboration skills.

What engineers make $500,000?

Senior machine learning operations (MLOps) engineers with extensive experience, specialized skills in cloud platforms, automation, and deployment often reach or exceed $500,000 annually in total compensation. High-level roles in tech companies or those with leadership responsibilities and advanced certifications tend to offer such salaries.

Which 3 jobs will survive AI?

For MLOps professionals, roles such as data scientists, machine learning engineers, and AI infrastructure engineers are expected to persist as AI adoption grows. These jobs require specialized skills in model development, deployment, and maintenance that complement automation. Continuous learning and expertise in tools like Kubernetes, cloud platforms, and version control are essential for long-term viability.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI director, often requiring advanced skills in data science, deep learning, and cloud platforms. These roles usually involve leadership, strategic planning, and extensive experience, and they may include bonuses or stock options that contribute to the total compensation. Such salaries are rare and generally found in large tech companies or specialized AI firms.

What are MLOps?

MLOps, short for Machine Learning Operations, is a set of practices that combines machine learning, DevOps, and data engineering to automate and streamline the deployment, monitoring, and maintenance of machine learning models in production. MLOps aims to improve collaboration between data scientists and operations teams, ensuring that models are robust, scalable, and easily updated. It covers the entire machine learning lifecycle, from data preparation to model training, deployment, and ongoing monitoring. By implementing MLOps, organizations can accelerate the development and deployment of reliable machine learning solutions.
What are popular job titles related to Mlops jobs in Riverside, CA? For Mlops jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Mlops jobs in Riverside, CA look for? The top searched job categories for Mlops jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Mlops jobs? Cities near Riverside, CA with the most Mlops job openings:
Mlops jobs near you

Data Scientist- Applied AI

Kia America

Irvine, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 22 days ago

Job description

At Kia, we're creating award-winning products and redefining what value means in the automotive industry. It takes a special group of individuals to do what we do, and we do it together. Our culture is fast-paced, collaborative, and innovative. Our people thrive on thinking differently and challenging the status quo. We are creating something special here, a culture of learning and opportunity, where you can help Kia achieve big things and most importantly, feel passionate and connected to your work every day.
Kia provides team members with competitive benefits including premium paid medical, dental and vision coverage for you and your dependents, 401(k) plan matching of 100% up to 6% of the salary deferral, and paid time off. Kia also offers company lease and purchase programs, company-wide holiday shutdown, paid volunteer hours, and premium lifestyle amenities at our corporate campus in Irvine, California.
Status
Exempt
General Summary
The Data Scientist plays an important role in executing data analysis for Kia North America's regional subsidiaries (KUS/KCA/KaGA/KMX). Kia's Big Data Analysis team leverages vast and diverse datasets to drive business improvements and insights. The role requires expertise in statistics, machine learning, and computer science to utilize high-performance compute clusters and perform reproducible analyses at scale. This position supports the application of data, analytics, automation, and responsible AI to advance Kia's business operations.
This role focuses on applying data science and AI techniques to analyze text and other unstructured data, build models, and generate insights that support business decisions. The role contributes to developing new AI- and data-driven products, capabilities, and analytical assets, treating data and models as products that can be used and scaled across the business.
Essential Duties and Responsibilities
1st Priority - 30%
Data Processing and Modeling
  • Assess the accuracy of new data sources
  • Understand the relationship between data sources and downstream use cases
  • Preprocess structured and unstructured data
  • Analyze large amounts of data to discover trends and patterns
  • Build, train, and evaluate machine learning and AI models, including modern NLP and GenAI approaches where appropriate.
  • Coordinate with cross-functional teams for feature engineering and data integration

2nd Priority - 30%
Model Evaluation, Iteration, and Insight Communication
  • Test and continuously improve the accuracy of statistical and machine learning models
  • Present information using Python notebooks and/or dashboards
  • Explain model behavior and performance in an intuitive manner to technical and non-technical audiences
  • Continuously monitor and validate production model performance
  • Treat models and analytical outputs as reusable products or services with clear ownership and quality standards

3rd Priority - 20%
Collaborate with IT on model deployment and MLOps setup
  • Build or contribute to REST APIs for model inference and result consumption
  • Partner with IT system developers on model deployment and MLOps best practices to ensure production readiness

4th Priority - 20%
Clear documentation, source code management, and reproducible analysis
  • Use git within GitLab
  • Create virtual environments to isolate project dependencies and requirements
  • Track model performance and hyperparameter configurations
  • Track data and model versioning

This list of essential responsibilities and duties is not exhaustive and may be supplemented and changed as necessary by management.
Qualifications/Education
  • Bachelor's degree in a technical or quantitative field required (e.g., Computer Science, Engineering, Mathematics, Statistics, or related field)
  • Master's degree in analytics, data science, or computer science preferred

Job Requirement
  • 3+ years of experience in data science preferred.
  • Strong foundation in machine learning required.
  • Strong Python and SQL skills required.
  • Hands-on experience building AI-powered features or products (e.g., NLP pipelines, GenAI features, AI agents); strong interest in continuous learning expected.
  • Familiarity with MLOps concepts (model versioning, deployment workflows, monitoring) preferred.
  • Ability to manage projects end-to-end and collaborate across technical and non-technical teams.
  • Experience querying databases and using programming languages such as Python and SQL
  • Experience using statistics and machine learning algorithms (deep learning a plus)
  • Experience with big data processing frameworks such as Spark (e.g., PySpark); experience with Hadoop ecosystem or cloud platforms (e.g., Databricks, AWS) preferred
  • Experience publishing results to stakeholders through dashboards (e.g. Power BI, MicroStrategy, Tableau)

Specialized Skills and Knowledge Required
  • Proficiency in Python and SQL
  • Knowledge and experience with NLP and related applied AI techniques (e.g., embeddings, retrieval, GenAI workflows)
  • Experience with common Python libraries for data analysis such as Pandas and NumPy
  • Experience with visualization libraries such as Matplotlib, Seaborn, Plotly, Bokeh and plotnine
  • Experience developing and evaluating statistical and machine learning models using libraries such as statsmodels and scikit-learn
  • Experience with deep learning frameworks such as PyTorch and TensorFlow preferred
  • Experience with big data processing tools such as Spark (e.g., PySpark); experience with Hadoop ecosystem or cloud platforms preferred
  • Strong data-driven problem-solving skills
  • Excellent written and verbal communication skills to coordinate across teams

Competencies
  • Care for People
  • Chase Excellence Every Day
  • Dare to Push Boundaries
  • Empower People to Act
  • Move Further Together

Pay Range
89,936 ~ 121,409.23
Pay will be based on several variables that are unique to each candidate, including but not limited to, job-related skills, experience, relevant education or training, etc.
Equal Employment Opportunities
KUS provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, ancestry, national origin, sex, including pregnancy and childbirth and related medical conditions, gender, gender identity, gender expression, age, legally protected physical disability or mental disability, legally protected medical condition, marital status, sexual orientation, family care or medical leave status, protected veteran or military status, genetic information or any other characteristic protected by applicable law. KUS complies with applicable law governing non-discrimination in employment in every location in which KUS has offices. The KUS EEO policy applies to all areas of employment, including recruitment, hiring, training, promotion, compensation, benefits, discipline, termination and all other privileges, terms and conditions of employment.
Disclaimer: The above information on this job description has been designed to indicate the general nature and level of work performed by employees within this classification and for this position. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job.
Employment Type

About Kia America

Sourced by ZipRecruiter

Industry

Motor vehicle manufacturing

Company size

501 - 1,000 Employees

Headquarters location

Irvine, CA, US

Year founded

1994

View All Kia America Jobs

Apply