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

Engineer II, AI/Machine Learning

Irvine, CA · On-site

$103K - $141K/yr

The AI/Machine Learning Engineer II will analyze data from various sources to develop computational models for disease diagnosis and prediction of critical events. Responsibilities : • Design and ...

... 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 ...

POSITION SUMMARY The AI/ML Engineer will participate in building, documenting, and refactoring ... machine learning workloads and production code. DISCLOSURE Our company provides equal employment ...

... 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 ...

Showing results 41-60

Machine Learning Engineer information

See Anaheim, CA salary details

$33K

$134.8K

$202.6K

How much do machine learning engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for machine learning engineer in Anaheim, CA is $134,809.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,300.00 and $162,300.00 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.

What are the most commonly searched types of Machine Learning Engineer jobs in Anaheim, CA? The most popular types of Machine Learning Engineer jobs in Anaheim, CA are:
What job categories do people searching Machine Learning Engineer jobs in Anaheim, CA look for? The top searched job categories for Machine Learning Engineer jobs in Anaheim, CA are:
What cities near Anaheim, CA are hiring for Machine Learning Engineer jobs? Cities near Anaheim, CA with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Anaheim, 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 $134,809 per year, or $64.8 per hour.

Machine Learning Engineer - LLMs

Hadrian Automation, Inc

Los Angeles, CA • On-site

$160K - $250K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 20 days ago


Job description

Hadrian - Manufacturing the Future
Hadrian is building autonomous factories that help aerospace and defense companies manufacture rockets, satellites, jets, and ships up to 10x faster and up to 2x cheaper. By combining advanced software, robotics, and full-stack manufacturing, we are reinventing how America produces its most critical parts.
We're accelerating our mission with the launch of Factory 3 in Mesa, Arizona, a 290,000-square-foot facility creating 350 new jobs. We are expanding rapidly to support thousands of future hires, launching Hadrian Maritime to expand into naval production, and introducing a Factory-as-a-Service model that delivers complete systems instead of individual parts.
Hadrian is backed by leading investors including T. Rowe Price, Lux Capital, Founders Fund, and Andreessen Horowitz, our fast-growing team is united around reindustrializing American manufacturing for the 21st century and beyond.
The Role
Copilot is our system for automating Design for Manufacturing (DFM) analysis and generating manufacturing processes. We work directly with some of the best operators in the world to identify high-impact opportunities to automate and augment with software.
Our team owns problems end-to-end: we design the software, define the manufacturing processes, and ensure they can be executed reliably in our factories. The work spans computational geometry, CAD/CAM integrations, high-performance systems, and full-stack web tooling. We execute whatever is required to deliver a working solution and best serve our users.
The DFM team within copilot is building the manufacturing data intelligence layer that serves as the tip of the spear for our automation stack. This platform ingests, interprets, and reasons over the full spectrum of manufacturing data (mechanical drawings, quality documentation, CAD data) and transforms it into structured, actionable information for the factory.
As a Senior Machine Learning Engineer, you will own the ML lifecycle for the language models that understand and reason about the content in manufacturing data packages.
What You'll Do
  • Research, develop, and deploy fine-tuned language models for document classification, key information extraction, table parsing, and multi-page/document reasoning
  • Work alongside the core engineering team to build and maintain annotation tooling, implement active learning loops, and engineer synthetic data augmentation strategies
  • Develop evaluation frameworks that extend beyond accuracy and CER, precisely quantifying system behavior and user impact
  • Collaborate with the other members of the machine learning team to set the technical and product roadmaps for the AI platform
  • Burn down the long tail, as every percentage point of accuracy maps to man-years of time savings at our scale
What We're Looking For
  • 5-8 years of professional AI/ML experience, with at least 2 years working directly with large language models (fine-tuning, RLHF/DPO, or pre-training), with special consideration for work with layout-aware models
  • Strong Python and PyTorch fluency: You've written custom training loops, loss functions, and data loaders from scratch when needed
  • Production deployment ownership: You've shipped models to production and have been responsible for endpoint and model health
  • MS or PhD in Computer Science, Electrical Engineering, or related field preferred; equivalent industry experience valued equally

Bonus Points
  • You have a passion for manufacturing and believe that the industry needs better software
  • Previously worked in aerospace, defense, or manufacturing, and have experience working with manufacturing data
  • Published research, achieved SOA results on relevant benchmarks, or contribute to open-source frameworks
  • Prior experience working in a high-ownership startup environment

Compensation
For this role, the target salary range is $160,000- $250,000(actual range may vary based on experience).
This is the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future. An employee's pay position within the salary range will be based on several factors, including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs.
Benefits for Full-time Employees
  • Medical, dental, vision, and life insurance plans for employees
  • 401k
  • Relocation support may be provided for certain situations, based on business need.
  • Flexible vacation policy
  • Equity
ITAR Requirements
To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.
Use of AI in hiring
Hadrian uses AI-assisted tools in our recruiting and hiring processes to help our team work more efficiently. This may include tools that help organize and analyze recruiting data, as well as an AI-powered notetaker that can record and transcribe interviews and help coordinate feedback. These tools support our team and are not used to make hiring decisions. All candidate evaluations and hiring decisions are performed by humans. If an interview will be recorded, you will be notified in advance and may opt out at any time with no impact on your candidacy. Candidate data processed through these tools is subject to the same protections described in our Privacy Policy.
Hadrian Is An Equal Opportunity Employer
It is the Company's policy to provide equal employment opportunity for all applicants and employees. The Company does not unlawfully discriminate on the basis of race inclusive of traits historically associated with race (including, but not limited to, hair texture and protective hairstyles, such as braids, locks and twists), color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, transgender status, national origin (including, in California, possession of a drivers license), ancestry, citizenship, age, physical or mental disability, height or weight, medical condition, family care status, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, exercise of reproductive rights, any other basis protected by local, state, or federal laws, or any combination of the above characteristics. When necessary, the Company also makes reasonable accommodations for disabled candidates and employees, including for candidates or employees who are disabled by pregnancy, childbirth, or related medical conditions.