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Machine Learning Engineer Jobs in Riverside, CA (NOW HIRING)

FieldAI

Software Engineer, MLOps

Irvine, CA · On-site

The MLOps Engineer will design and maintain infrastructure for machine learning systems, collaborating closely with engineering teams to ensure effective deployment and monitoring of ML models.

Turion Space

Lead AI Engineer

Irvine, CA

$110K - $144K/yr

Description The Lead AI Engineer will be responsible for defining and driving the AI strategy ... Design, develop, and deploy advanced AI models and algorithms, including machine learning, deep ...

FieldAI

Senior Software Engineer, MLOps

Irvine, CA · On-site

$129K - $171K/yr

They are seeking a skilled Senior MLOps Engineer to design and maintain the infrastructure supporting machine learning systems in robotics applications, collaborating with various engineering teams ...

Pwc

AI Engineer

Irvine, CA · On-site

$55K - $187K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials ...

Pwc

AI Engineer

Irvine, CA · On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Building ...

Pwc

AI Solutions Engineering Delivery Lead

Irvine, CA

$110K - $144K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

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Showing results 41-60

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Riverside, CA

Machine Learning Engineer information

See Riverside, CA salary details

$32.9K

$134.3K

$201.9K

How much do machine learning engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for machine learning engineer in Riverside, CA is $134,341.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,900.00 and $161,700.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Riverside, CA? The most popular types of Machine Learning Engineer jobs in Riverside, CA are:
What are popular job titles related to Machine Learning Engineer jobs in Riverside, CA? For Machine Learning Engineer jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Riverside, CA look for? The top searched job categories for Machine Learning Engineer jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Machine Learning Engineer jobs? Cities near Riverside, CA with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Riverside, CA as of July 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $134,341 per year, or $64.6 per hour.

1.65 Senior Machine Learning Platform Engineer

FieldAI

Irvine, CA • On-site

$110K - $152K/yr

Full-time

Re-posted 25 days ago

Job description

Job Summary:
FieldAI is a company based in Irvine focused on building risk-aware, reliable AI systems for robotics. The Senior Machine Learning Platform Engineer will own the infrastructure for the Field-insight Foundation Model, ensuring its transition from research to production while optimizing performance and cost.
Responsibilities:
• Design and manage scalable ML infrastructure with IaC tools (Terraform, CloudFormation).
• Develop and optimize cloud-based pipelines for training, evaluation, and inference on multimodal datasets.
• Build and operate data systems for large-scale video ingestion, indexing, and storage.
• Maintain MLOps workflows for versioning, experiment tracking, reproducibility, and CI/CD.
• Ensure reliability and observability with monitoring, logging, and alerting.
• Collaborate with AI/ML Engineers to productionize workflows.
• Optimize infrastructure for performance and cost across cloud and edge.
• Enforce best practices in security, compliance, and maintainability.
• Mentor and manage junior engineers, providing technical guidance and career development.
Qualifications:
Required:
• Bachelor’s/Master’s in Computer Science, Engineering, or related field (or equivalent experience).
• 4+ years of industry experience in ML infrastructure or platform engineering.
• Strong coding skills in Python/TypeScript and a strong foundation in software engineering best practices.
• Proven experience with distributed systems, cloud platforms (AWS preferred), containerization and orchestration (Docker, Kubernetes/EKS, Ray), and serverless.
• Hands-on experience building ML pipelines for distributed training and large-scale inference.
• Strong knowledge of data management at scale, including preprocessing and retrieval of video/image datasets.
• Proficiency with CI/CD pipelines, infrastructure-as-code (Terraform, CloudFormation), and automation.
• Familiarity with MLOps tools (MLflow, Kubeflow, Airflow).
• Experience with system monitoring and observability in production.
Preferred:
• Experience with vector databases (OpenSearch, Pinecone, Weaviate) for indexing and retrieval.
• Familiarity with distributed training frameworks (Horovod, DDP/FSDP, DeepSpeed, Ray).
• Hands-on experience with GPU orchestration and auto-scaling (Karpenter, SageMaker, EKS).
• Experience with agentic AI deployment workflows, orchestration frameworks, and retrieval-augmented generation.
• Strong knowledge of security and compliance in ML and cloud environments.
Company:
FieldAI is building general robot intelligence for the physical world. Founded in 2023, the company is headquartered in Mission Viejo, USA, with a team of 201-500 employees. The company is currently Early Stage.

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