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Internship Machine Learning Engineer Jobs in Lawndale, CA

We are currently hiring both full-time and interns to join our R&D team. Responsibilities ... engineering, or mathematics * 2-3 years of relevant experience in building deep learning solutions ...

Machine Learning Engineer

El Segundo, CA · On-site

$77.60 - $176/hr

R0244683 Machine Learning Engineer The Opportunity: As a programmer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct statistical ...

Machine Learning Engineer II

Los Angeles, CA · On-site +1

$105K - $143K/yr

Machine Learning Engineers (this role) who focus on modeling and algorithmic innovation * Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training ...

Machine Learning Engineer II

Los Angeles, CA · On-site

$105K - $143K/yr

In this role you will work with a high performing team of applied scientists, machine learning engineers, and software development engineers that has delivered a number of AI/ML systems to production ...

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 ...

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

Internship Machine Learning Engineer information

See Lawndale, CA salary details

$26.2K

$43.7K

$90.3K

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

As of Aug 19, 2026, the average yearly pay for internship machine learning engineer in Lawndale, CA is $43,679.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,300.00 and $47,200.00 per year, depending on experience, location, and employer.

What does an internship machine learning engineer do?

An Internship Machine Learning Engineer works alongside experienced engineers to help develop, test, and deploy machine learning models. Their responsibilities may include cleaning and preparing data, writing code for model training, evaluating model performance, and contributing to research tasks. Interns often learn to use popular frameworks such as TensorFlow or PyTorch and gain hands-on experience with real-world datasets. This role is designed to help students or recent graduates apply their academic knowledge to practical problems while developing industry-relevant skills.

What types of projects and responsibilities can I expect as an internship machine learning engineer?

As an Internship Machine Learning Engineer, you will typically support the development, testing, and deployment of machine learning models under the guidance of senior engineers. Your responsibilities may include data preprocessing, exploratory data analysis, implementing algorithms, and evaluating model performance. You'll often collaborate closely with data scientists, software engineers, and product managers, gaining exposure to real-world workflows and tools. This hands-on experience is invaluable for building technical skills and understanding how machine learning solutions are integrated into larger products.

What are the key skills and qualifications needed to thrive as an internship machine learning engineer, and why are they important?

To excel as an Internship Machine Learning Engineer, you typically need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, often supported by coursework or relevant project experience. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is common, along with proficiency in data processing libraries. Curiosity, strong problem-solving abilities, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can contribute meaningfully to projects, adapt to new challenges, and collaborate productively in a rapidly evolving technical environment.

What is the difference between Internship Machine Learning Engineer vs Data Scientist Intern?

AspectInternship Machine Learning EngineerData Scientist Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, data analysis, programming
Work EnvironmentDeveloping ML models, coding, testingData analysis, visualization, reporting
Employer & Industry UsageTech companies, startups, AI firmsTech, finance, healthcare, consulting

Internship Machine Learning Engineers focus on developing and testing machine learning models, often requiring programming and basic ML knowledge. Data Scientist Interns analyze data, create visualizations, and generate insights. Both roles are common in tech and data-driven industries, but ML Engineer internships emphasize model deployment, while Data Science internships focus on data analysis and reporting.

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

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

Machine Learning Engineer

Voxelcloud

Los Angeles, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 24 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.