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

Yum! Brands

Sr Machine Learning Engineer

Irvine, CA

$112K - $154K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 · On-site

$112K - $154K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Layup Parts

Machine Learning Engineer

Huntington Beach, CA · On-site

$120 - $185/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given ...

Mach Industries

Machine Learning Engineer

Huntington Beach, CA · On-site

$120K - $160K/yr

  • Medical

  • Life

  • Retirement

As a Machine Learning Engineer, you will own and scale the training, data, and edge-inference backbone that every vision and multi-sensor model on our product lines depends on for detection, tracking ...

Yum

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Layup Parts

Machine Learning Engineer

Huntington Beach, CA · On-site

$120K - $185K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given ...

Layup Parts

Machine Learning Engineer

Huntington Beach, CA · On-site

$120K - $185K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given ...

Turion Space

Machine Learning Engineer

Irvine, CA

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

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 ...

Bespoke Labs

Machine Learning Engineer

Pomona, CA · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

... 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 ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

... 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 ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

... 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 ...

FieldAI

2.53 3D Machine Learning Engineer

Irvine, CA · On-site

They are seeking a 3D Machine Learning Engineer to design, implement, and maintain advanced 3D machine learning models for processing reality capture data, contributing to automated progress tracking ...

FieldAI

Senior Machine Learning Engineer

Irvine, CA

$180K - $215K/yr

... engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. What You'll Get To Do Machine Learning ...

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Showing results 1-20

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

Machine Learning Engineer information

See Irvine, CA salary details

$33.8K

$138.2K

$207.7K

How much do machine learning engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for machine learning engineer in Irvine, CA is $138,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,900.00 and $166,400.00 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 Irvine, CA?

The most popular types of Machine Learning Engineer jobs in Irvine, CA are:

What are popular job titles related to Machine Learning Engineer jobs in Irvine, CA?

For Machine Learning Engineer jobs in Irvine, CA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Irvine, CA look for?

The top searched job categories for Machine Learning Engineer jobs in Irvine, CA are:

What cities near Irvine, CA are hiring for Machine Learning Engineer jobs?

Cities near Irvine, CA with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Irvine, CA as of August 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 100% In-person job distribution, with an average salary of $138,220 per year, or $66.5 per hour.

Machine Learning Engineer II

Niagara Bottling, LLC

Diamond Bar, CA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 22 days ago

Niagara Bottling rating

7.8

Company rating: 7.8 out of 10

Based on 114 frontline employees who took The Breakroom Quiz

100th of 438 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.
Machine Learning Engineer II
As a Machine Learning Engineer II, you will design, build next-generation predictive and prescriptive maintenance systems utilizing Azure Machine Learning Studio from end to end. Drawing on industrial sensor data and machine PLC , you will develop cutting-edge models that detect failure signatures before they occur and prescribe optimized corrective actions.
You will own the end-to-end industrial ML lifecycle. You will design, train, and optimize supervised and unsupervised architectures to accurately predict equipment Remaining Useful Life (RUL), detect complex anomalies, and deploy prescriptive Agentic AI decision workflows. Once validated, you will deploy these models to low-latency cloud and edge endpoints, seamlessly integrating predictions with plant dashboards, End points Applications and CMMS workflows. Finally, you will establish automated MLOps pipelines in Azure ML Studio to continuously monitor data drift and trigger zero-downtime model retraining as physical factory environments evolve.
This is a high-impact & cross-functional engineering role requiring strong technical depth, system-level thinking, and the ability to communicate complex solutions effectively to diverse audiences including operations (Manufacturing plants), IT, systems Engineering, and executive leadership.
Key Responsibilities
1. Advanced ML Modeling & Algorithmic
  • Supervised & Unsupervised Learning: Build robust classifiers for fault diagnosis and regression models for Remaining Useful Life (RUL) estimation. Expertly handle highly imbalanced datasets where failure labels are rare.
  • Agentic AI & Prescriptive Systems: Develop multi-agent workflows that reason over asset health data, parse digital manuals via RAG (Retrieval-Augmented Generation), interact with operational APIs, and generate automated outputs.
  • Utilizing XGBoost, Random Forests, LSTMs, and Autoencoders-to process sensor streams and PLC data for predictive maintenance and real-time anomaly detection. leverage techniques like Isolation Forests, One-Class SVMs, Dynamic Time Warping, and PCA to build scalable models that monitor asset health, classify process quality, and drive automated decision-making.

2. Production-Grade MLOps & Infrastructure
  • Robust Data Engineering: Standardize, clean, and enrich raw, unstructured, or missing sensor telemetry and PLC tag data.
  • Scalable ML Pipelines: Build and maintain scalable, reproducible training and inference pipelines (using MLflow, Kubeflow, or Azure Machine Learning).
  • Edge & Cloud Deployment: Deploy models across hybrid environments, optimizing for cloud (Azure) as well as low-latency.
  • Distributed Compute Tuning: Optimize model training and throughput, leveraging GPU-accelerated training and efficient serialization for massive datasets.

3. Systems Integration & Cross-Functional Impact
  • High-Fidelity Code: Deliver highly optimized, production-grade, modular software in Python and C++ accompanied by strict unit testing, and clean documentation.
  • Technical Communication: Bridge the gap between data science and physical operations. Clearly articulate complex ML mechanics, decision boundaries, and model limitations to plant managers, IT directors, and executive leadership.

Qualifications & Deep Technical Requirements
Technical Skills (Must-Haves):
  • Frameworks & Libraries: Deep expertise in PyTorch or TensorFlow, alongside standard data science libraries (Scikit-Learn, NumPy, Pandas, SciPy).
  • Production Programming: Exceptional software development skills in Python (writing optimized, vectorized code) ,Java Script, C/C++ & R
  • Modern MLOps & Cloud: Hands-on experience with containerization (Docker/Kubernetes), distributed processing (PySpark/Databricks), and cloud architectures, ideally Microsoft Azure.
  • Data Handling: Mastery of SQL, NoSQL, and time-series databases (e.g., InfluxDB, TimescaleDB) containing millions of streaming data points.

  • This position 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.

This position embodies the values of Niagara's LIFE competency model, focusing on the following key drivers of success:
  • Lead Like an Owner
  • Manages a safe working environment, accurately documents safety-related training, and effectively communicates safety incidents
  • Provides strategic input and oversight to departmental projects
  • Makes data-driven decisions and develops sustainable solutions
  • Skilled in reducing costs and managing timelines while prioritizing long-run impact over short-term wins
  • Makes decisions by putting overall company success first before department/individual success
  • Leads/facilitates discussions to get positive outcomes for the customer
  • Makes strategic decisions that prioritize the needs of the customer over departmental/individual goals
  • InnovACT
  • Continuously evaluates existing programs and processes, and develops new initiatives to increase efficiency and reduce waste
  • Creates, monitors, and responds to departmental performance metrics to drive continuous improvement
  • Champions responsible adoption of Agentic AI and intelligent automation to improve reliability, speed, decision quality, and waste reduction while maintaining safety and governance.
  • Communicates a clear vision, organizes resources effectively, and adjusts the strategy as needed when managing change
  • Find a Way
  • Demonstrates ability to think analytically and synthesize complex information
  • Effectively delegates technical tasks to subordinates
  • Works effectively with departments, vendors, and customers to achieve organizational success
  • Identifies opportunities for collaboration in strategic ways
  • Empowered to be Great
  • Makes hiring decisions primarily based on culture fit and attitude, and secondarily based on technical expertise
  • Engages in long-term talent planning
  • Provides opportunities for the development of all direct reports
  • Understands, identifies, and addresses conflict within own team and between teams

Work Experience/KSA's
  • Required:
  • Education: Bachelor's degree in Computer Science, Data Science, Electrical/Mechanical Engineering, Mathematics, or related quantitative field (Master's or PhD with an ML focus is highly preferred).
  • Strong proficiency in Python and modern machine learning frameworks such as PyTorch and/or TensorFlow
  • Experience working across multiple modalities, with expertise in one or more of:
    • Natural Language Processing: LLMs, text classification, information extraction, retrieval systems, agentic applications, or related areas.
  • Experience training, fine-tuning, evaluating, and deploying machine learning models in production environments.
  • Experience designing evaluation methodologies, benchmarking systems, and model performance metrics.
  • Experience with MLOps tools and practices (Docker, Kubernetes, CI/CD for ML, MLflow, etc.)
  • Experience with cloud platforms such as Google Cloud Platform (preferred), AWS, or Azure, including ML infrastructure, workflow orchestration, storage, and database services.

Preferred:
  • Masters or PhD degrees are preferred.

  • 5-7 years - Experience in Python, R, or another programming language
  • 5-7 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 or PhD 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
$100,464.14 - $145,673.02 / 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 fertility benefits for IVF and fertility preservation plus adoption, surrogacy, and Doula reimbursements
  • Income protection including Life and AD&D, short and long-term disability, critical illness and an accident plan
  • Special discount programs including pet plans, pre-paid legal services, identity theft, car rental, airport parking, etc.
  • Tuition reimbursement, college savings plan and scholarship opportunities
  • And more!

https://careers.niagarawater.com/us/en/benefits
* *Los Angeles County applicants only** Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers, the California Fair Chance Act, and any other applicable local and state laws.
Any employment agency, person or entity that submits a rés

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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