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

Voxelcloud

Machine Learning Engineer

Los Angeles, CA · On-site

MS degree in computer science, engineering, or mathematics * 2-3 years of relevant experience in building deep learning solutions for computer vision problems * Proficient with at least one major ...

Warnerbros

Senior Machine Learning Engineer

Burbank, CA · On-site

$111K - $153K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do Warner Bros. Discovery (WBD) is home to the world's most iconic entertainment, news, and sports ...

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Machine Learning Engineer information

See Burbank, CA salary details

$33.7K

$137.7K

$207K

How much do machine learning engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for machine learning engineer in Burbank, CA is $137,747.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,600.00 and $165,800.00 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 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 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 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 Burbank, CA?

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

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

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

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

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

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Burbank, CA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $137,747 per year, or $66.2 per hour.

Machine Learning Engineer

Los Angeles, CA • On-site

Voxelcloud
Medical Equipment and Supplies Manufacturing • 11 - 50 employees
Learn more about Voxelcloudexternal

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 17 days ago

Job description

Company Description
Founded in 2016, VoxelCloud, Inc. is a Los Angeles-based worldwide leader in AI analysis of medical images. Backed by Sequoia and Tencent. We help healthcare providers make better/earlier diagnoses and related clinical decisions, improving outcomes for all. http://www.voxelcloud.ai
Job Description
The R&D team (located in Los Angeles, CA) is involved with research and development of innovative solutions to medical imaging applications, including disease detection/quantification in medical scans, disease risk stratification, image synthesis, text report mining, and more! We are currently hiring both full-time and interns to join our R&D team.
Responsibilities:
  • Develop deep learning models for prototyping and production purposes according to product feature request
  • Design, implement and test model experiments using major deep learning frameworks
  • Document experiments findings and results with supporting summary statistics for peer discussion and review (Confluence)
  • Provide insights to data collection and annotation and collaborate with the data team for in-house data management and labelling
  • Write production and deployment code (dockerization), iterate deployed models for optimal performance and inference speed
  • Conduct methodology research in deep learning to drive scalable, real-time implementation

Qualifications
Basic Qualifications
  • MS degree in computer science, engineering, or mathematics
  • 2-3 years of relevant experience in building deep learning solutions for computer vision problems
  • Proficient with at least one major deep learning framework, preferably TensorFlow/Pytorch
  • Proficient in Python
  • Good CS fundamentals in data structures and algorithm
  • Detail-oriented, well organized and self-motivated with a continuous drive to learn, explore and be challenged
  • Work well in teams and communicate ideas clearly

Preferred Qualifications
  • PhD degree in computer science, engineering, or mathematics
  • 3-5 years of relevant experience in building deep learning solutions for computer vision problems
  • Hands-on experience with state-of-the-art object detection (e.g., RetinaNet, Mask RCNN, CenterNet), semantic segmentation (e.g., U-Net, deeplab), and image classification models (e.g., ResNet, DenseNet).
  • Track record of publications in CV and medical image analysis is a plus
  • Hands-on experience with model optimization (e.g., network quantization and mixed-precision training) is a plus
  • Prior experience with medial images is a plus

Additional Information
We Offer...
  • An outstanding start-up culture;
  • Transparent, collaborative work environment;
  • Competitive compensation
  • Excellent Medical, Dental, and Vision coverage
  • 401k, paid Vacation and Holiday

All your information will be kept confidential according to EEO guidelines.

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