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Machine Learning Developer Intern Jobs in Los Angeles, CA

Mach Industries

Machine Learning Engineer

Huntington Beach, CA · On-site

$120K - $160K/yr

  • Medical

  • Life

  • Retirement

As a Machine Learning Engineer, you will own and scale the training, data, and edge-inference backbone that every vision and multi-sensor model on our product lines depends on for detection, tracking ...

Prodege LLC

Staff Machine Learning Engineer

El Segundo, CA

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

We're looking for a Staff Machine Learning Engineer who loves shipping production ML systems, owning complex technical problems end-to-end, and partnering closely with Product, Data Engineering, and ...

Layup Parts

Machine Learning Engineer

Huntington Beach, CA · On-site

$120K - $185K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Layup Parts

Machine Learning Engineer

Huntington Beach, CA

$120K - $185K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Layup Parts

Machine Learning Engineer

Huntington Beach, CA · 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 ...

Voxelcloud

Machine Learning Engineer

Los Angeles, CA

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

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 ...

Turion Space

Machine Learning Engineer

Irvine, CA

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

As a Machine Learning Integration Engineer, you will help rapidly prototype, mature, and monitor ML/CV solution that are integral to Turion's Space Domain Awareness data products. You will work on ...

Voxelcloud

Machine Learning Engineer

Los Angeles, CA · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

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 ...

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Showing results 41-60

All JobsMachine Learning Developer Intern JobsMachine Learning Developer Intern Jobs in Los Angeles, CA

Machine Learning Developer Intern information

See Los Angeles, CA salary details

$27.5K

$45.9K

$94.8K

How much do machine learning developer intern jobs pay per year?

As of Aug 15, 2026, the average yearly pay for machine learning developer intern in Los Angeles, CA is $45,884.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,000.00 and $49,600.00 per year, depending on experience, location, and employer.

How do machine learning developer interns typically collaborate with data scientists and engineers during their internship?

Machine Learning Developer Interns often work closely with data scientists to understand the problem domain, gather relevant datasets, and select appropriate models. They also collaborate with software engineers to integrate machine learning solutions into existing systems, ensuring scalability and performance. Regular communication through stand-up meetings, code reviews, and collaborative platforms is common, allowing interns to learn best practices and receive feedback on their work. This teamwork not only enhances technical skills but also provides valuable exposure to real-world deployment and project lifecycle management.

What does a machine learning developer intern do?

A Machine Learning Developer Intern assists with developing, testing, and implementing machine learning models and algorithms under the guidance of experienced engineers or data scientists. Their tasks may include data preprocessing, model training, evaluating model performance, and helping deploy models into production environments. Interns often collaborate with team members to solve real-world problems using machine learning techniques and may also assist in researching new methodologies or optimizing existing solutions. This role provides hands-on experience in coding, data analysis, and applying theoretical concepts to practical scenarios.

What are the key skills and qualifications needed to thrive as a machine learning developer intern?

To thrive as a Machine Learning Developer Intern, you need a solid understanding of programming (especially Python), statistics, and machine learning concepts, often supported by coursework or relevant project experience. Familiarity with ML frameworks like TensorFlow or PyTorch, and tools such as Jupyter Notebooks and version control systems like Git, is typically expected. Strong analytical thinking, eagerness to learn, and effective communication help interns contribute to team projects and adapt quickly. These skills are essential for solving real-world problems, collaborating with teams, and building a foundation for a successful career in machine learning.

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

AspectMachine Learning Developer InternData Scientist Intern
Required CredentialsTypically pursuing or recently completed a degree in Computer Science, Data Science, or related fields; knowledge of programming languages like Python or JavaSimilar educational background; strong skills in statistics, programming, and data analysis
Work EnvironmentHands-on experience with ML models, algorithms, and software development in tech or research settingsData analysis, visualization, and interpretation in business or research contexts
Employer & Industry UsageTech companies, startups, research labs focusing on AI/ML projectsBusiness, finance, healthcare, and research organizations analyzing large datasets

Both roles involve working with data and programming, but Machine Learning Developer Interns focus more on building and deploying ML models, while Data Scientist Interns emphasize data analysis and insights. The roles often overlap, especially in tech environments, but their core tasks differ slightly.

What cities near Los Angeles, CA are hiring for Machine Learning Developer Intern jobs?

Cities near Los Angeles, CA with the most Machine Learning Developer Intern job openings:

Machine Learning Developer Intern jobs near you

Machine Learning Engineer

Mach Industries

Huntington Beach, CA • On-site

$120K - $160K/yr

Full-time

Medical, Life, Retirement

Posted 18 days ago

Job description

About Mach Industries
Founded in 2023, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition.
Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security.
The Role
Mach Industries is building an AI-forward autonomy stack for contested environments where GPS and other sensing are unavailable or unreliable. As a Machine Learning Engineer, you will own and scale the training, data, and edge-inference backbone that every vision and multi-sensor model on our product lines depends on for detection, tracking, search, navigation, targeting, and automatic target recognition. This is a broad, high-ownership role: you'll stand up the data and training infrastructure that lets the autonomy team iterate fast, generate synthetic data to cover the long tail, and get research-grade models running in real time on embedded hardware in flight. We are generalists, so you'll move fluidly between infrastructure, modeling, and deployment.
Key Responsibilities
  • Own and evolve the training and data infrastructure the autonomy team builds on: ingestion from flight/sim/HITL, curation and mining, labeling/QA workflows, dataset versioning (DVC/Parquet), and reproducible dataset builds.
  • Stand up and scale training/eval infrastructure: distributed multi-GPU training, experiment tracking, a model registry, and CI-based evaluation with regression gates plus automated field-data to retrain to validate to redeploy loops.
  • Deploy and optimize models for real-time edge inference on Jetson-class hardware (quantization/pruning, TensorRT/ONNX Runtime); profile CPU/GPU and hit tight latency, throughput, and SWaP targets.
  • Build and improve models across the portfolio as a hands-on IC: detection, segmentation, tracking, target/area search, classification/ATR, and multi-sensor fusion for EO/IR and auxiliary sensing.
  • Generate and manage synthetic data at scale (simulation + domain randomization) to cover long-tail and degraded conditions and close sim-to-real gaps.
  • Instrument runtime health, drift detection, and graceful degradation, and wire model-performance metrics back into the data and retraining loop.
  • Live close to flight data with visualization, triage, and root-cause tooling so the team can go from field logs to insight and model updates rapidly.
  • Partner with other autonomy disciplines across perception, localization, embedded, and flight-test to take capabilities from prototype to sim to HITL to flight to deployment.

Required Qualifications
  • Strong generalist software engineering: Python for ML and tooling, plus production C++ on Linux; profiling, optimization, and rigorous testing discipline.
  • Proven experience building ML data and training pipelines end to end: dataset construction, labeling/QA, augmentation, experiment tracking, and reproducible training.
  • Hands-on training and fine-tuning in PyTorch across modern detection/segmentation/tracking architectures (CNN/Transformer).
  • Edge and real-time deployment: model compression (INT8/FP16), runtime optimization (TensorRT/ONNX Runtime), and meeting latency/SWaP constraints on embedded GPU (Jetson-class) hardware.
  • Data and MLOps infrastructure: SQL/Parquet, dataset/versioning tools, CI-based validation, and scalable multi-GPU training.
  • BS/MS/PhD in CS/EE/Robotics or similar, or equivalent experience, with a track record shipping ML models to production or hardware. Senior candidates: deeper ownership of training/data infrastructure at scale.

Preferred Qualifications
  • Synthetic data generation and simulation (e.g. Unreal/Isaac, domain randomization) and demonstrated sim-to-real transfer.
  • EO/IR imagery experience and working with real flight/test data in challenging, degraded, or contested environments.
  • Multi-modal perception and fusion (EO/IR + radar/LiDAR/RF) at the feature or decision level.
  • Detection/tracking/search at scale; active learning and data-mining strategies for long-tail coverage.
  • CUDA backends for performance debugging; ROS 2; NVIDIA Jetson deployment pipelines.
  • Drift/dataset-shift monitoring, robustness and rare-event testing, long-horizon reliability metrics.
  • Distributed training frameworks and cloud ML platforms (e.g. SageMaker); Docker for reproducibility; Rust for systems tooling.

Disclosures
This position may require access to information protected under U.S. export control laws and regulations, including the Export Administration Regulations (EAR) and the International Traffic in Arms Regulations (ITAR). Please note that any offer for employment may be conditioned on authorization to receive software or technology controlled under these U.S. export control laws and regulations without sponsorship for an export license.
Mach participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offers may vary based on (but not limited to) work experience, education and training, critical skills, and business considerations. Highly competitive equity grants are included in most offers and are considered part of Mach's total compensation package. Mach offers benefits such as health insurance, retirement plans, and opportunities for professional development.
Mach is an equal opportunity employer committed to creating a diverse and inclusive workplace. 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. If you'd like to defend the American way of life, please reach out!

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