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Full Time Machine Learning Data Annotation Jobs in Los Angeles, CA

... maintain annotation tooling, implement active learning loops, and engineer synthetic data ... Benefits for Full-time Employees * Medical, dental, vision, and life insurance plans for employees ...

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ... You'll work closely with our engineering team to transform raw data into actionable intelligence ...

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ... You'll work closely with our engineering team to transform raw data into actionable intelligence ...

Machine Learning Engineer

Torrance, CA · On-site

$160K - $250K/yr

Our homebuilt DFM platform analyzes design prints and CAD models to make logical, data-driven ... Benefits for Full-time Employees * Medical, dental, vision, and life insurance plans for employees ...

Our homebuilt DFM platform analyzes design prints and CAD models to make logical, data-driven ... Benefits for Full-time Employees * Medical, dental, vision, and life insurance plans for employees ...

... data pipelines, and software systems for training, inference, labeling, and evaluation • ... Machine Learning, including ownership of projects throughout the entire ML Lifecycle • ...

Machine Learning Engineer

Torrance, CA · On-site

$160K - $250K/yr

Our homebuilt DFM platform analyzes design prints and CAD models to make logical, data-driven ... Benefits for Full-time Employees * Medical, dental, vision, and life insurance plans for employees ...

Overview Spotter empowers the world's best Creators with capital, data, and insights to scale their ... What You'll Do You'll develop machine learning models that move beyond experimentation and into ...

... data pipelines, and software systems for training, inference, labeling, and evaluation • ... Machine Learning, including ownership of projects throughout the entire ML Lifecycle • ...

... machine learning and data approaches - including to 'do more with less' (quantity and quality of) data and data annotations. o Manage and make ongoing improvements to our data annotation platform and ...

Showing results 21-40

Full Time Machine Learning Data Annotation information

See Los Angeles, CA salary details

$40.4K

$132.3K

$211.7K

How much do full time machine learning data annotation jobs pay per year?

As of Aug 8, 2026, the average yearly pay for full time machine learning data annotation in Los Angeles, CA is $132,252.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,100.00 and $146,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a full time machine learning data annotation specialist, and why are they important?

To thrive as a Full Time Machine Learning Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency in specialized annotation platforms, spreadsheet tools, and sometimes knowledge of Python or labeling frameworks is typically required. Reliability, patience, and effective communication are valuable soft skills for ensuring accuracy and collaborating with team members. These skills and qualities are crucial because they directly impact the quality of training data, which is essential for developing effective machine learning models.

What is a full time machine learning data annotation job?

Full time machine learning data annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Data annotators play a crucial role in ensuring that AI systems learn from high-quality, accurately labeled datasets. These positions often require attention to detail, consistency, and sometimes familiarity with the subject matter or specialized tools. Full-time roles may be remote or onsite and can span industries like autonomous vehicles, healthcare, retail, and more.

What are some common challenges faced by machine learning data annotators, and how are these typically addressed within a team?

Machine learning data annotators often encounter challenges such as maintaining consistency in labeling, handling ambiguous data, and meeting tight deadlines for large datasets. Teams usually address these by establishing clear annotation guidelines, conducting regular training sessions, and implementing quality assurance processes like peer reviews and spot checks. Collaboration with data scientists and project managers is also common, ensuring that annotators can ask questions and clarify uncertainties, leading to higher-quality labeled data and a supportive work environment.

What is the difference between Full Time Machine Learning Data Annotation vs Data Labeling Specialist?

AspectFull Time Machine Learning Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; some roles prefer technical certificationsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or office; focused on labeling tasks
Industry UsageUsed across AI/ML companies, tech firms, and startupsCommon in AI/ML, data services, and outsourcing companies
Job FocusCreating labeled datasets for machine learning modelsAnnotating data such as images, videos, or text for AI training

Full Time Machine Learning Data Annotation involves creating high-quality labeled datasets for AI models, often requiring technical understanding. Data Labeling Specialists focus on annotating data accurately, typically with less emphasis on technical skills. Both roles are essential in AI development but differ mainly in scope and technical complexity.

What are the most commonly searched types of Machine Learning Data Annotation jobs in Los Angeles, CA? The most popular types of Machine Learning Data Annotation jobs in Los Angeles, CA are:
What are popular job titles related to Full Time Machine Learning Data Annotation jobs in Los Angeles, CA? For Full Time Machine Learning Data Annotation jobs in Los Angeles, CA, the most frequently searched job titles are:
What job categories do people searching Full Time Machine Learning Data Annotation jobs in Los Angeles, CA look for? The top searched job categories for Full Time Machine Learning Data Annotation jobs in Los Angeles, CA are:
What cities near Los Angeles, CA are hiring for Full Time Machine Learning Data Annotation jobs? Cities near Los Angeles, CA with the most Full Time Machine Learning Data Annotation job openings:

Machine Learning Engineer - Vision

Hadrian Automation, Inc

Los Angeles, CA • On-site

$160K - $250K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 17 days ago


Job description

Hadrian - Manufacturing the Future
Hadrian is building autonomous factories to reindustrialize America. By combining AI, advanced software, robotics, and full-stack manufacturing, we help aerospace and defense companies build rockets, satellites, aircraft, ships, and other mission-critical systems up to 10x faster and at significantly lower cost.
Following our $1.37B Series D at a $7.87B valuation, Hadrian is rapidly expanding our manufacturing footprint, launching new capabilities across welding, casting, forging, electronics, additive manufacturing, and more, while scaling our Factory-as-a-Service platform to transform how critical products are built.
Backed by leading investors including JPMorgan Chase, Valor Equity Partners, Andreessen Horowitz, Founders Fund, 137 Ventures, Lux Capital, T. Rowe Price, and Morgan Stanley, we're building the future of American manufacturing-and looking for exceptional people to help make it happen.
If you're ready to take on the most challenging and rewarding work of your career while helping create American manufacturing jobs for generations to come, you're exactly who we're looking for.
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 detection and segmentation models at the core of our manufacturing intelligence pipeline.
What You'll Do
  • Research, develop, and deploy cutting-edge object detection and segmentation models for layout analysis, document understanding, and semantic part understanding
  • 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 to capture metrics that extend beyond mAP/IoU, 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 experience building and shipping computer vision models, with an emphasis on detection and/or segmentation
  • Deep expertise in modern architectures using transformer backbones (ViT, Swin, etc...)
  • 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.