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Data Engineer Ml Jobs in Riverside, CA (NOW HIRING)

FieldAI

Agentic AI/ML Engineer, Multimodal

Irvine, CA · On-site

We go beyond typical data-driven approaches or pure transformer-only architectures, combining ... As an AI/ML Engineer on the FiFM team, you will drive research and model development for one of ...

Qcells

Applied AI Engineer

Irvine, CA · On-site

$160K - $190K/yr

Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related field. Relevant certifications in AI, ML, or cloud platforms are a plus.

Qcells

Applied AI Engineer

Irvine, CA · On-site

$160K - $190K/yr

Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related field. Relevant certifications in AI, ML, or cloud platforms are a plus.

First American

Senior Applied ML Engineer

Santa Ana, CA

$129K - $189K/yr

Develop end-to-end ML and LLM pipelines, covering data ingestion, scripting, automated workflows ... WHAT YOU'LL BRING * 5+ years of experience in machine learning engineering, with a proven track ...

First American

Senior Applied ML Engineer

Santa Ana, CA · On-site

$129K - $189K/yr

Develop end-to-end ML and LLM pipelines, covering data ingestion, scripting, automated workflows ... WHAT YOU'LL BRING * 5+ years of experience in machine learning engineering, with a proven track ...

Qcells Europe

Applied AI Engineer

Irvine, CA · On-site

$121K - $145K/yr

Required : • Bachelor's or Master's degree in Computer Science, Data Science, Artificial ... Preferred : • Relevant certifications in AI, ML, or cloud platforms are a plus. Company : Qcells ...

FieldAI

Agentic AI/ML Engineer

Irvine, CA · On-site

We go beyond typical data-driven approaches or pure transformer-only architectures, combining ... As an Agentic AI/ML Engineer, you will build agentic solutions that turn FieldAI's data and tooling ...

LHH US

Director of Engineering, AI/ML

Brea, CA · On-site

$200K - $320K/yr

This role is essential in building and managing a world-class team of ML Engineers and Data/ML Scientists. Your expertise will guide teams in building reliable systems that deliver impactful ...

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Showing results 1-20

All JobsData Engineer Ml JobsData Engineer Ml Jobs in Riverside, CA

Data Engineer Ml information

See Riverside, CA salary details

$48K

$172.2K

$254K

How much do data engineer ml jobs pay per year?

As of Jun 11, 2026, the average yearly pay for data engineer ml in Riverside, CA is $172,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $139,300.00 and $177,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Engineer ML, and why are they important?

To thrive as a Data Engineer ML, you need strong programming skills (especially in Python or Scala), knowledge of data modeling, and a solid foundation in database technologies, typically supported by a degree in computer science or a related field. Familiarity with big data frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and ETL tools, as well as relevant certifications, is highly beneficial. Excellent problem-solving abilities, teamwork, and clear communication help you collaborate with data scientists and stakeholders effectively. These skills are essential for building robust data pipelines and infrastructure that enable scalable, high-quality machine learning solutions.

What does a Data Engineer ML do?

A Data Engineer ML (Machine Learning) is responsible for designing, building, and maintaining the data pipelines and infrastructure necessary for machine learning applications. They clean, process, and organize large datasets to ensure data quality and accessibility for data scientists and ML engineers. In addition, they may work on deploying machine learning models to production environments and optimizing data workflows for efficiency and scalability.

What is the difference between Data Engineer Ml vs Data Scientist?

AspectData Engineer MlData Scientist
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science certifications
Work EnvironmentBuilding data pipelines, managing databasesAnalyzing data, creating models
Employer & Industry UsageTech companies, finance, healthcareResearch institutions, tech firms, finance

Data Engineer Ml focuses on developing and maintaining data infrastructure and pipelines, while Data Scientists analyze data and build predictive models. Both roles often collaborate but serve different functions within data teams.

How do Data Engineer ML roles typically collaborate with data scientists and machine learning engineers on projects?

Data Engineer ML professionals work closely with data scientists and machine learning engineers by building and maintaining robust data pipelines, ensuring clean and reliable datasets are readily available for modeling and analysis. They often participate in meetings to understand model requirements, help optimize data storage for performance, and support the deployment of machine learning models into production environments. Effective collaboration involves continuous communication to troubleshoot data issues, implement data validation, and scale solutions as project needs evolve. This teamwork ensures that data-driven projects move efficiently from experimentation to deployment.
What are popular job titles related to Data Engineer Ml jobs in Riverside, CA? For Data Engineer Ml jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Data Engineer Ml jobs in Riverside, CA look for? The top searched job categories for Data Engineer Ml jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Data Engineer Ml jobs? Cities near Riverside, CA with the most Data Engineer Ml job openings:
Data Engineer Ml jobs near you
Infographic showing various Data Engineer Ml job openings in Riverside, CA as of June 2026, with employment types broken down into 2% As Needed, 61% Full Time, 36% Part Time, and 1% Temporary. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $172,158 per year, or $82.8 per hour.
Sr. Engineer Data Science & Agentic AI

Sr. Engineer Data Science & Agentic AI

Niagara Bottling, LLC

Diamond Bar, CA • On-site

$119K - $143K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago

Niagara Bottling rating

7.9

Company rating: 7.9 out of 10

Based on 110 frontline employees who took The Breakroom Quiz

79th of 381 rated food and drinks producers

Job description

At Niagara, we're looking for Team Members who want to be part of achieving our mission to provide our customers the highest quality most affordable bottled water.
Consider applying here, if you want to:
  • Work in an entrepreneurial and dynamic environment with a chance to make an impact.
  • Develop lasting relationships with great people.
  • Have the opportunity to build a satisfying career.

We offer competitive compensation and benefits packages for our Team Members.
Sr. Engineer Data Science & Agentic AI
As a Data Science & Agentic AI Sr. Engineer , you will develop, design, implement, and deliver advanced data science, machine learning, and agentic AI products for all aspects of Machine Maintenance. The role creates novel predictive and prescriptive maintenance solutions, including AI agents and multi-agent workflows that can retrieve knowledge, reason over asset and maintenance data, use approved tools and APIs, and recommend or automate maintenance actions with appropriate human oversight. You will perform data wrangling, exploratory, descriptive, predictive, prescriptive, and agent-enabled analysis and visualization on both a recurring and ad hoc basis in support of the Projects Manager and the Maintenance user base. The Data Science & Agentic AI Sr. Engineer will identify new opportunities for intelligent process automation, Agentic AI, KPIs, visualizations, reports, dashboards, and decision-support products by aligning organizational insight requests with leadership's strategic objectives.
Detailed Description
  • Full Spectrum Data Science and Agentic AI Management

  • Lead the entire data science, machine learning, and agentic AI lifecycle, from problem definition and data collection through model/agent design, deployment, monitoring, governance, and continuous improvement.

  • Ensure seamless integration and coordination across data pipelines, ML/DL models, LLM applications, agentic workflows, APIs, and business processes, optimizing for safety, scalability, efficiency, and business impact.

  • Establish robust monitoring mechanisms for deployed models and AI agents, enabling proactive identification of performance, reliability, drift, safety, cost, and governance issues.

  • ML/DL and Agentic AI Strategy Development:

  • Define and execute the overall machine learning, deep learning, and Agentic AI strategy aligned with business goals, maintenance reliability priorities, and enterprise technology standards.

  • Work closely with stakeholders to identify opportunities for advanced analytics, predictive modeling, AI agents, and intelligent workflow automation that improve maintenance reliability, decision quality, and operational efficiency.

  • Agentic AI Strategy and Execution:

  • Define and lead the Agentic AI roadmap for predictive maintenance, maintenance knowledge management, work-order triage, troubleshooting, root-cause analysis, and prescriptive reliability workflows.

  • Design, build, and deploy AI agents and multi-agent workflows using large language models (LLMs), retrieval-augmented generation (RAG), vector search, tool/function calling, workflow orchestration, and secure API integrations.

  • Integrate agentic workflows with CMMS/EAM, maintenance, asset, IoT, historian, PLC/SCADA, cloud, and enterprise data platforms while maintaining human-in-the-loop controls for higher-risk actions.

  • Establish AgentOps, LLMOps, and MLOps practices for prompt/version management, agent evaluation, observability, guardrails, traceability, cost monitoring, model drift detection, and continuous improvement.

  • Implement agentic AI safety, privacy, and security controls, including least-privilege access, data protection, prompt-injection mitigation, approval gates, audit trails, and responsible AI governance.

  • ML/DL and Agentic AI Implementation and Execution:

  • Drive large-scale data science, ML/DL, and Agentic AI projects that leverage data transformation, machine learning models, LLM applications, and intelligent workflow automation.

  • Develop first-class predictive maintenance tools, AI agents, and insights for customers by balancing data complexity, coding/visualization platforms, reliability requirements, risk controls, and client demands.

  • Automate and streamline projects, reports, maintenance workflows, and agent-enabled decision processes to increase efficiency, scalability, and adoption.

  • Develop alternative procedures, data products, agent tools, and processing methods to optimize data interactions, human-machine collaboration, and new insights.

  • Contribute to storyboarding activities, developing recommendations for an executive-level audience, and producing leadership-quality deliverables

  • Manage and review ad hoc automation, AI agent, analytics, and information product support requests.

  • Collaboration: Work closely with project management teams, IT professionals, reliability engineers, maintenance leaders, and business stakeholders to identify opportunities for AI agents, ML models, and automation to enhance maintenance execution and project management.

  • Documentation: Document project requirements, methodologies, architecture decisions, agent workflows, evaluation results, risks, and outcomes. Prepare technical reports, presentations, and user guides to effectively communicate AI/ML/Agentic AI solutions to stakeholders.

  • Research and Innovation: Stay updated with the latest advancements in AI/ML, Agentic AI, LLMs, RAG, vector search, orchestration frameworks, and industrial automation. Conduct research and experiments to explore new approaches and improve existing models and agents.

  • Ethical, Legal, and Responsible AI Considerations: Ensure compliance with ethical standards and legal requirements when dealing with sensitive data, privacy, bias, explainability, autonomy, human oversight, and potential misuse of AI/ML models or AI agents.

  • Training and Knowledge Sharing: Share expertise in AI/ML, Agentic AI, responsible automation, and insights with colleagues, stakeholders, and team members. Conduct training sessions or workshops to facilitate effective utilization of machine learning programs, AI agents, libraries, and governance practices.

  • Knowledge of data acquisition and data Engineering for manufacturing

  • Please note that this job description is not designed to contain a comprehensive list of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without prior notice.

Data Science & Agentic AI Manager is estimated to travel 10-30%
  • Please note this job description is not a full list of activities, duties or responsibilities required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without prior notice.

Work Experience/KSA's
Required:
  • 5-7 years - Experience in Python, R, or another programming language

  • 5-7 years - Experience with TensorFlow, PyTorch, scikit-learn, or comparable ML frameworks

  • 3-5 years - Experience in Industrial ML, Automation, Data Science, AI, or related fields

  • 3-5 years - Experience with cloud computing platforms such as AWS, Azure, or GCP

  • 2-4 years - Experience with natural language processing (NLP), LLM applications, prompt engineering, or retrieval-augmented generation (RAG)

  • 2-4 years - Experience designing or deploying Agentic AI solutions, AI agents, RAG applications, LLM-powered workflows, or intelligent automation

  • 2-4 years - Experience with agent orchestration and LLM application frameworks or platforms such as LangChain, LlamaIndex, Microsoft Semantic Kernel, AutoGen, Azure AI Foundry, OpenAI API, or equivalent

  • 3-5 years - Experience with Deep Learning, Computer Vision, Reinforcement Learning, or advanced predictive modeling

  • 2-4 years - Experience with ethical, legal, privacy, security, and responsible AI considerations in machine learning and agentic AI systems

  • 2-4 years - Experience implementing AI guardrails, prompt/agent evaluation, telemetry, human-in-the-loop review, and model or agent monitoring

  • *Experience may include a combination of work experience and education

Preferred:
  • 7-10 years - Experience in Python, R, or another programming language

  • 7-10 years - Experience with TensorFlow, PyTorch, scikit-learn, or comparable ML frameworks

  • 5-7 years - Experience in Industrial ML, Automation, Data Science, AI, or related fields

  • 5-7 years - Experience with cloud computing platforms such as AWS, Azure, or GCP

  • 3-5 years - Experience with natural language processing (NLP), LLM applications, prompt engineering, or retrieval-augmented generation (RAG)

  • 3-5 years - Experience leading production Agentic AI, LLM, RAG, or multi-agent orchestration initiatives in industrial, manufacturing, maintenance, reliability, or enterprise operations environments

  • 5-7 years - Experience with Deep Learning, Computer Vision, Reinforcement Learning, or advanced predictive modeling

  • 3-5 years - Experience with ethical, legal, privacy, security, and responsible AI considerations in machine learning and agentic AI systems

  • 3-5 years - Experience with AgentOps/LLMOps practices, including monitoring, evaluation, versioning, safety testing, audit trails, and cost/performance optimization

  • *Experience may include a combination of work experience and education

Preferred Competencies and Skills
  • Proficiency in Azure ML Studio and related tools for model development, deployment, and monitoring.

  • Proficiency in Agentic AI and LLM application development, including prompt engineering, RAG, vector search/embeddings, function/tool calling, and agent workflow orchestration.

  • Experience with Agentic AI frameworks or platforms such as LangChain, LlamaIndex, Microsoft Semantic Kernel, AutoGen, CrewAI, Azure AI Foundry, OpenAI API, or equivalent.

  • Ability to design secure AI agent integrations with APIs, databases, CMMS/EAM platforms, cloud services, and industrial data sources while enforcing least-privilege access and approval gates.

  • Ability to evaluate and monitor AI agent performance using offline and online evaluations, trace logs, quality metrics, guardrails, human feedback, and incident response processes.

  • Understanding of Responsible AI, privacy, prompt-injection risks, model/tool misuse, auditability, and governance for autonomous or semi-autonomous AI agents.

  • Proficiency in using query languages such as SQL, Hive, Pig. Etc.

  • Proficiency in, but not limited to:

  • Microsoft Office Applications - Word, Excel, PowerPoint, Outlook, Project, Visio, etc.

  • Proficiency in applied statistical skills, such as distributions, statistical testing, regression, etc.

  • Basic understanding of data acquisition and processing tools and techniques and developing algorithms on common platforms to generate outputs

  • Scripting and programming skills such as Python, SQL, JavaScript, C++, C#, or API-based integration for analytics, automation, and AI agent tool development

  • Basic understanding of PLC/SCADA systems such SIEMENS S7, ALLEN BRADLEY, BnR, Edge data Management, etc.

  • Understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, decision forests, gradient boosting, neural networks, and LLM-based approaches

  • Preferred experience with common data science and AI toolkits, such as R, Weka, Python, NumPy, Matplotlib, Pandas, MATLAB, Azure ML, and LLM/agent development libraries

  • Able to translate data, model outputs, and AI agent recommendations into actionable decisions for senior management

  • Strong analytical and problem-solving skills

  • Self-motivated with a proven record of taking initiative

  • Able to work with minimal supervision

  • Detail-oriented with excellent oral and written communication skills

  • Able to execute tasks in a very dynamic and ever-changing environment

Education
Minimum Required:
  • Bachelor's Degree in Computer Science, Data Science, Artificial Intelligence, Industrial/Automation Engineering, or other related fields or equivalent experience

  • Preferred:

  • Master's Degree in Computer Science, Data Science, Artificial Intelligence, Industrial/Automation Engineering, or related field

Certification/License:
  • Required: N/A

  • Preferred: N/A

Typical Compensation Range
Pay Rate Type: Salary
$111,766.36 - $159,267.07 / Yearly
Benefits
Our Total Rewards package is thoughtfully designed to support both you and your family:
Regular full-time team members are offered a comprehensive benefits package, while part-time, intern, and seasonal team members are offered a limited benefits package.
  • Paid Time Off for holidays, sick time, and vacation time
  • Paid parental and caregiver leaves
  • Medical, including virtual care options
  • Dental
  • Vision
  • 401(k) with company match
  • Health Savings Account with company match
  • Flexible Spending Accounts
  • Expanded mental wellbeing benefits including free counseling sessions for all team members and household family members
  • Family Building Benefits including enhanced fertil...

What Niagara Bottling employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Niagara Bottling logo

About Niagara Bottling

Sourced by ZipRecruiter

Niagara Bottling, LLC has been family owned and operated since 1963. Niagara is a leading bottled water manufacturer in the U.S., supplying major retailers across the nation. Nielsen +/biNyDGcAS61OV0GIrHcWTOCFo= Nielsen is a global leader in audience measurement, data and analytics, shaping the future of media. Measuring behavior across all channels and platforms to discover what audiences love, we empower our clients with trusted intelligence that fuels action. Do you want to move the industry forward with Nielsen? Our people are the driving force. Your thoughts, ideas and expertise can propel us forward. Whether you have fresh thinking around maximizing a new technology or you see a gap in the market, we are here to listen and take action. Our team is made strong by a diversity of thoughts, experiences, skills, and backgrounds. You'll enjoy working with smart, fun, curious colleagues, who are passionate about their work. Come be part of a team that motivates you to do your best work! NielsenIQ /xHzLYOL7B5gJKeErHR5OpVt2Os= NielsenIQ is a global measurement and data analytics company providing the most complete and trusted view of consumers and markets in 90 countries covering 90% of the world's population. Focusing on consumer-packaged goods manufacturers and FMCG and retailers, we enable customers to defy what's possible. How? We combine unparalleled datasets, pioneering technology, and the industry's top talent to create insights that unlock innovation. Join us and change the landscape. Nike weB0VQ7iUwaCHWNipwHEhUU5oFo= Our purpose is to unite the world through sport to create a healthy planet, active communities, and an equal playing field for all. In order to stay at the top of our game, we're always looking to level-up with outstanding people who provide the kind of above-and-beyond service that inspires Nike fans for life! NOCD qMdV2+zQfKcKckWjOX3hDGP8fkM= NOCD is the #1 telehealth provider for the treatment of obsessive-compulsive disorder (OCD). OCD is one of the most severe, prevalent, and misunderstood mental health conditions. NOCD creates access to online therapy for people with OCD through our telehealth platform. In the NOCD app, members can quickly access and schedule live, face-to-face video therapy sessions with our national network of licensed therapists that specialize in Exposure and Response Prevention Therapy (ERP) - considered the gold standard" in OCD treatment. At NOCD, we help people reclaim their lives with clinically proven OCD treatment, by removing barriers to OCD care, and reducing the stigma associated with OCD. We're changing the world and need other like-minded individuals to accelerate and expand our efforts.

Industry

Food and beverage stores

Company size

5,001 - 10,000 Employees

Headquarters location

Diamond Bar, CA, US

Year founded

1963

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