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Senior Machine Learning Engineer Jobs in Riverside, CA

Senior Machine Learning Engineer

Irvine, CA ยท On-site

$111.60K - $153.20K/yr

Access on-demand professional development resources that allow you to hone existing skills and learn new ones "I can succeed as a Senior Machine Learning Engineer at Capital Group." You will join our ...

Senior Machine Learning Engineer

Irvine, CA

$112.20K - $154K/yr

Access on-demand professional development resources that allow you to hone existing skills and learn new ones "I can succeed as a Machine Learning Engineer at Capital Group" We are seeking a strong ...

Senior Machine Learning Engineer

Irvine, CA

$112.20K - $154K/yr

... Machine Learning Engineering team to build the next generation of AI products at Capital Group - including agentic systems, LLM-powered workflows, and the platform that ensures they are safe ...

As a Machine Learning Integration Engineer, you will help rapidly prototype, mature, and monitor ML/CV solution that are integral to Turion's Space Domain Awareness data products. You will work on ...

As a 3D Machine Learning Engineer , you will focus on designing, implementing, training, and maintaining cutting-edge 3D and multimodal machine learning models that process reality capture data such ...

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ...

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ...

Senior Machine Learning Platform Engineer

Irvine, CA ยท On-site

$112.20K - $154K/yr

We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results ...

Senior Machine Learning Platform Engineer

Irvine, CA ยท On-site

$112.20K - $154K/yr

We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results ...

Senior Engineer, Machine Learning

Irvine, CA ยท On-site

$125K - $150K/yr

The Senior Engineer, Machine Learning will be responsible for developing state-of-the-art audio and vision models to be deployed on edge devices. We are looking for candidates at the cutting edge of ...

Senior Engineer, Machine Learning

Irvine, CA ยท On-site

$125K - $150K/yr

The Senior Engineer, Machine Learning will be responsible for developing state-of-the-art audio and vision models to be deployed on edge devices. We are looking for candidates at the cutting edge of ...

The Senior Engineer, Machine Learning will be responsible for developing state-of-the-art audio and vision models to be deployed on edge devices. We are looking for candidates at the cutting edge of ...

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Cultivate organizational excellence by mentoring senior technical talent, fostering research ...

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Senior Machine Learning Engineer information

See Riverside, CA salary details

$62.1K

$132K

$191.4K

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

As of May 29, 2026, the average yearly pay for senior machine learning engineer in Riverside, CA is $132,033.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,000.00 and $149,700.00 per year, depending on experience, location, and employer.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are popular job titles related to Senior Machine Learning Engineer jobs in Riverside, CA? For Senior Machine Learning Engineer jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Engineer jobs in Riverside, CA look for? The top searched job categories for Senior Machine Learning Engineer jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Senior Machine Learning Engineer jobs? Cities near Riverside, CA with the most Senior Machine Learning Engineer job openings:
Infographic showing various Senior Machine Learning Engineer job openings in Riverside, CA as of May 2026, with employment types broken down into 1% Internship, 88% Full Time, 8% Part Time, 1% Temporary, and 2% Contract. Highlights an 78% Physical, 8% Hybrid, and 14% Remote job distribution, with an average salary of $132,033 per year, or $63.5 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Capital Group

Irvine, CA โ€ข On-site

$111.60K - $153.20K/yr

Full-time

Medical, Life, Retirement

Posted 15 days ago


Job description

"I can be myself at work."
You are more than a job title. We want you to feel comfortable doing great work and bringing your best, authentic self to everything you do. We value your talents, traditions, and uniqueness-and we're committed to fostering a strong sense of belonging in a respectful workplace.
We intentionally seek diverse perspectives, experiences, and backgrounds, investing in a culture designed to celebrate differences. We believe that belonging leads to better outcomes and a stronger community of associates united by our mission. At Capital, we live our core values every day: Integrity, Client Focus, Diverse Perspectives, Long-Term Thinking, and Community.
"I can influence my income."
You want to feel recognized at work. Your performance will be reviewed annually, and your compensation will be designed to motivate and reward the value that you provide. You'll receive a competitive salary, bonuses and benefits. Your company-funded retirement contribution will factor in salary and variable pay, including bonuses.
"I can lead a full life."
You bring unique goals and interests to your job and your life. Whether you're raising a family, you're passionate about where you volunteer, or you want to explore different career paths, we'll give you the resources that can set you up for success.
  • Enjoy generous time-away and health benefits from day one, with the opportunity for flexible work options
  • Receive 2-for-1 matching gifts for your charitable contributions and the opportunity to secure annual grants for the organizations you love
  • Access on-demand professional development resources that allow you to hone existing skills and learn new ones

"I can succeed as a Senior Machine Learning Engineer at Capital Group."
You will join our Machine Learning Engineering team to build the next generation of AI products at Capital Group - including agentic systems, LLM-powered workflows, and the platform that ensures they are safe, governed, and reliable in production.
You will operate at the intersection of production ML, GenAI and agentic workflows, and governed data infrastructure. In this high-impact role, you will help define how enterprise-grade AI systems are designed, deployed, and operated. You will work with a high degree of autonomy, mentor junior engineers, and drive engineering standards across projects built on Databricks, AWS, and agent-based architectures.
What You Will Do
AI Infrastructure & Production Systems
  • You architect and operate end-to-end production AI systems - designing, building, deploying, monitoring, and managing the full lifecycle of ML and GenAI workloads

  • You develop production-grade cloud-native environments optimized for AI/ML model training, serving, and orchestration

  • You establish and evangelize engineering standards, reference patterns, and reusable platform components for AI services across the firm

  • You design scalable inference pipelines, including retraining loops, drift detection, evaluation harnesses, and observability

Agentic Workflows & GenAI
  • You build agentic systems with multi-step reasoning, orchestration, and tool/function calling, including MCP-based integrations

  • You develop evaluation harnesses, traces, and replay tooling so agent behavior is observable and continuously improvable

  • You apply advanced prompt engineering, evaluation frameworks, guardrails, and human-in-the-loop patterns to deliver reliable LLM-powered features

  • You drive the agentic SDLC, defining how agents are designed, tested, evaluated, deployed, and monitored as first-class production assets

Databricks & AWS Platform Engineering
  • You build solutions on Databricks (Unity Catalog, MLflow, Spark) and AWS, leveraging native AI capabilities for model training, serving, and governance

  • You use Infrastructure as Code to provision and manage cloud-native, scalable, and secure environments

  • You integrate with vector stores, graph databases, Redis, DynamoDB, and ElastiCache to enable retrieval, memory, and state for AI applications

ML Engineering & Delivery
  • You build REST and streaming APIs to expose ML and agentic capabilities to downstream products and platforms

  • You apply advanced prompt engineering, RAG patterns, fine-tuning, and model selection aligned to specific use cases

  • You optimize performance, cost, and computational efficiency across distributed compute workloads

  • You develop and tune ML models and perform data cleaning, feature engineering, preprocessing, and exploratory analysis

Governance, Risk & Collaboration
  • You embed data lineage, access controls, audit trails, and responsible AI practices into every system you build

  • You partner with product, business, and data teams to translate ambiguous problems into well-scoped agentic solutions

  • You lead code reviews, set engineering standards, mentor junior engineers, and propose scalable solutions

"I am the person Capital Group is looking for."
  • You have 7+ years of professional software engineering with strong proficiency in Python and core software engineering fundamentals

  • You have experience building and operating production ML systems end-to-end, including deployment, monitoring, and lifecycle management

  • You have hands-on experience with AWS and/or Databricks, including native AI/ML capabilities and Infrastructure as Code

  • You have experience integrating GenAI and LLMs using advanced prompt engineering and evaluation techniques

  • You have experience developing APIs (REST and streaming endpoints) and familiarity with MCP (Model Context Protocol)

  • You have strong ML fundamentals, including algorithms, evaluation metrics, and model tuning

  • You have a bachelor's degree in information technology, computer science, or a related field.

  • You have experience with data handling, including data cleaning, feature engineering, preprocessing, and exploratory data analysis

  • You demonstrate the ability to operate autonomously on complex technical initiatives

  • You have experience with CI/CD and DevOps, including containerization, deployment pipelines, and testing frameworks

Strongly Preferred Skills
  • You have experience with agentic architectures, including multi-step reasoning, orchestration frameworks, tool/function calling, and agent evaluation

  • You have experience with data infrastructure for AI, including vector stores, graph databases, Redis, DynamoDB, and ElastiCache

  • You have experience with data governance tools and practices such as Unity Catalog, data lineage, access controls, and audit trails

  • You have experience with distributed computing, including Spark and large-scale data processing

  • You have experience designing human-in-the-loop systems, including guardrails, LLM output evaluation, and responsible AI practices

"I can apply in less than 4 minutes."
You've reviewed this job posting and you're ready to start the candidate journey with us. Apply now to move to the next step in our recruiting process. If this role isn't what you're looking for, check out our other opportunities and join our talent community.
"I can learn more about Capital Group."
At Capital Group, the success of the people who invest with us depends on the people in whom we invest. That's why we offer a culture, compensation and opportunities that empower our associates to build successful and prosperous careers. Through nine decades, our goal has been to improve people's lives through successful investing. We know that our history is a testament to the strength of the people we hire. More than 9,000 associates in 30+ offices around the world help our clients and each other grow and thrive every day. Find us on LinkedIn, Instagram, YouTube and Glassdoor.
Southern California Base Salary Range: $201,683-$322,693
In addition to a highly competitive base salary, per plan guidelines, restrictions and vesting requirements, you also will be eligible for an individual annual performance bonus, plus Capital's annual profitability bonus plus a retirement plan where Capital contributes 15% of your eligible earnings.
You can learn more about our compensation and benefits here.
* Temporary positions in the United States are excluded from the above mentioned compensation and benefit plans.
We are an equal opportunity employer, which means we comply with all federal, state and local laws that prohibit discrimination when making all decisions about employment. As equal opportunity employers, our policies prohibit unlawful discrimination on the basis of race, religion, color, national origin, ancestry, sex (including gender and gender identity), pregnancy, childbirth and related medical conditions, age, physical or mental disability, medical condition, genetic information, marital status, sexual orientation, citizenship status, AIDS/HIV status, political activities or affiliations, military or veteran status, status as a victim of domestic violence, assault or stalking or any other characteristic protected by federal, state or local law.