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Contract Machine Learning Engineer Jobs in Azusa, CA

Machine Learning Engineer

Huntington Beach, CA ยท On-site

$120K - $185K/yr

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 ...

Senior Machine Learning Engineer

Burbank, CA

$111K - $153K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do ... Shape the team's feature-store strategy - feature contracts, backfills, and freshness SLAs - and ...

Machine Learning Engineer

Los Angeles, CA ยท On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Showing results 21-40

Contract Machine Learning Engineer information

See Azusa, CA salary details

$32K

$131K

$196.9K

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

As of Aug 22, 2026, the average yearly pay for contract machine learning engineer in Azusa, CA is $131,002.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,300.00 and $157,700.00 per year, depending on experience, location, and employer.

What is a contract machine learning engineer?

A Contract Machine Learning Engineer is a professional who builds and deploys machine learning models on a temporary or project-based basis. They typically work with companies seeking specialized expertise in data science, model development, or AI integration without committing to a full-time hire. Responsibilities may include data preprocessing, model training, algorithm optimization, and deployment. Contract roles allow for flexibility and are often remote, making them ideal for businesses with short-term AI needs or startups looking to scale their machine learning capabilities quickly.

What are the typical day-to-day responsibilities of a contract machine learning engineer?

As a Contract Machine Learning Engineer, your daily tasks usually involve gathering and preprocessing data, building and fine-tuning machine learning models, and collaborating with software engineers and product managers to integrate your models into production systems. You may also meet with clients or internal teams to gather requirements and provide technical insights, as well as document and present your findings to stakeholders. Work is typically project-based and may require a high degree of independence, flexibility, and adaptability. This dynamic environment often exposes you to a variety of industries and technical challenges, making each project unique and providing valuable experience for professional growth.

What are the key skills and qualifications needed to thrive in the contract machine learning engineer position, and why are they important?

To thrive as a Contract Machine Learning Engineer, you need a strong background in machine learning algorithms, data preprocessing, statistical analysis, and proficiency in programming languages such as Python or R, often supported by a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience using cloud platforms (AWS, Google Cloud, Azure) or certifications in these areas are common requirements. Excellent problem-solving, communication, and time management skills are vital, especially when working with cross-functional teams and managing multiple projects remotely. These skills ensure effective delivery of high-quality, scalable machine learning solutions within tight project timelines and diverse client environments.

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

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

Infographic showing various Contract Machine Learning Engineer job openings in Azusa, CA as of August 2026, with employment types broken down into 1% As Needed, 61% Full Time, 32% Part Time, 1% Temporary, and 5% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $131,002 per year, or $63 per hour.

Machine Learning Engineer

Layup Parts

Huntington Beach, CA โ€ข On-site

$120K - $185K/yr

Full-time

Posted 18 days ago


Job description

At Layup Parts, we're developing the technology that will build the future.  

We're a manufacturing technology company replacing months of lead time with days, using proprietary software, automation, and advanced manufacturing systems built for speed. Our customers are inventing what's next, in aerospace, defense, robotics, and beyond. To keep up with them, manufacturing has to change. That's what we're building. 

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 design, and extracting structured data out of existing documentation. We're looking for someone who has trained custom models on large, parameter-rich datasets, ideally with a geometric or spatial component, and who is energized by problems in that space specifically. 

What You'll Do
  • Train and iterate on custom ML models using Layup's internal manufacturing and design data 
  • Build models that estimate cost and predict design complexity or manufacturing difficulty from part geometry 
  • Develop models that generate or assist in generating new designs based on historical design data 
  • Build pipelines to extract structured data (specs, dimensions, material callouts, etc.) from existing engineering documents and drawings 
  • Evaluate and select modeling approaches suited to geometric, spatial, and other structured data, rather than text-based problems 
  • Work closely with engineering and manufacturing teams to source, clean, and label internal datasets 
  • Own model performance end-to-end, from data pipeline through training, evaluation, and deployment into internal tools 
  • Continuously identify new opportunities where custom models could improve design, estimation, or manufacturing workflows 
What We're Looking For
  • Experience training custom models beyond basic labeling or fine-tuning workflows 
  • Experience with advanced object detection at minimum; data classification experience is a strong plus 
  • Experience with geometry-based modeling is highly preferred 
  • Experience working with large, parameter-rich datasets 
  • Strongest fit is someone whose background is in structured, spatial, or geometric data problems rather than natural language or LLM-centric work 
Bonus Points
  • Experience training geometry-specific models 
  • CAD experience 
  • Manufacturing experience 

Final compensation is based on your experience, skills, and what you bring to the table.  

  • Full Benefits Package: Medical, dental, and vision coverage, short- and long-term disability insurance, company-paid life insurance  
  • Equity Option Grants 
  • 401k plan 
  • Paid Time Off:  Unlimited PTO + 9 Federal Holidays 

Equal Opportunity 

Layup is an equal-opportunity employer. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, creed, religion, sex, gender identity, sexual orientation, national origin, disability, uniform service, Veteran status, age, or any other protected characteristic per federal, state, or local law, including those with a criminal history, in a manner consistent with the requirements of applicable state and local laws, including the CA Fair Chance Initiative for Hiring Ordinance.  

ITAR Requirements  

To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here. 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.