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Internship Machine Learning Engineer New Grad Jobs in Anaheim, CA

Turion Space

Machine Learning Engineer

Irvine, CA

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 ...

Crowe LLP

Machine Learning Engineer

Costa Mesa, CA

$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 ...

Hermeus

Manufacturing Engineer, New Grad

Los Angeles, CA · On-site

$91K - $112K/yr

About the Role Hermeus is seeking a hands-on, highly motivated New Grad Manufacturing Engineer to ... Hands-on experience through internships, research, capstone projects, student competition teams ...

Crowe LLP

Machine Learning Engineer

Los Angeles, CA · 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 ...

Hermeus

Manufacturing Engineer, New Grad

Los Angeles, CA · On-site

$91K - $112K/yr

About the Role Hermeus is seeking a hands-on, highly motivated New Grad Manufacturing Engineer to ... Hands-on experience through internships, research, capstone projects, student competition teams ...

Hermeus

Manufacturing Engineer, New Grad

Los Angeles, CA

$91K - $112K/yr

About the Role Hermeus is seeking a hands-on, highly motivated New Grad Manufacturing Engineer to ... Hands-on experience through internships, research, capstone projects, student competition teams ...

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All JobsMachine Learning Engineer New Grad JobsInternship Machine Learning Engineer New Grad JobsInternship Machine Learning Engineer New Grad Jobs in Anaheim, CA

Internship Machine Learning Engineer New Grad information

See Anaheim, CA salary details

$26.7K

$44.6K

$92.1K

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

As of Aug 22, 2026, the average yearly pay for internship machine learning engineer new grad in Anaheim, CA is $44,581.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,000.00 and $48,200.00 per year, depending on experience, location, and employer.

What does an internship machine learning engineer new grad do?

An Internship Machine Learning Engineer New Grad typically works on developing, testing, and optimizing machine learning models under the guidance of senior engineers or data scientists. Their responsibilities often include data preprocessing, feature engineering, model training, and evaluating model performance. They may also collaborate with cross-functional teams to integrate models into production or contribute to research projects. This role provides hands-on experience with real-world data and the opportunity to learn industry-standard tools and practices.

What are the key skills and qualifications needed to thrive as an internship machine learning engineer new grad?

To thrive as an Internship Machine Learning Engineer New Grad, you need a strong grasp of programming (especially Python), machine learning algorithms, data structures, and a relevant degree or coursework in computer science or a related field. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is typically expected. Strong analytical thinking, problem-solving abilities, and a willingness to learn make you stand out in this position. These skills enable you to contribute effectively to projects, quickly adapt to new challenges, and support innovative solutions in a fast-evolving field.

What types of projects do machine learning engineer interns typically work on?

Machine Learning Engineer interns often work on hands-on projects such as data preprocessing, model development, and conducting experiments to validate algorithms under the guidance of senior engineers. These projects might include building prototypes, optimizing existing machine learning models, or supporting data collection and annotation efforts. Interns are expected to collaborate closely with data scientists, software engineers, and product teams to align their work with real business needs. This experience not only helps interns build technical skills but also provides insight into how machine learning solutions are integrated into larger products or services.

What is the difference between Internship Machine Learning Engineer New Grad vs Machine Learning Engineer?

AspectInternship Machine Learning Engineer New GradMachine Learning Engineer
Required CredentialsTypically pursuing or recently completed a Bachelor's or Master's in CS, Data Science, or related fieldsBachelor's or higher in CS, Data Science, or related fields; often requires some professional experience
Work EnvironmentTemporary, learning-focused internship, often part-time or summerFull-time professional role in a team, responsible for deploying ML models and projects
Employer & Industry UsageInternships offered by tech companies, startups, and research labs; industry-wideFull-time roles in tech, finance, healthcare, and other sectors utilizing ML

The main difference between an Internship Machine Learning Engineer New Grad and a Machine Learning Engineer is experience level and job responsibilities. Internships are temporary, learning-focused positions for recent graduates or students, while full-time Machine Learning Engineers handle ongoing projects, deployment, and optimization of ML models in a professional setting.

What are popular job titles related to Internship Machine Learning Engineer New Grad jobs in Anaheim, CA?

For Internship Machine Learning Engineer New Grad jobs in Anaheim, CA, the most frequently searched job titles are:

What job categories do people searching Internship Machine Learning Engineer New Grad jobs in Anaheim, CA look for?

The top searched job categories for Internship Machine Learning Engineer New Grad jobs in Anaheim, CA are:

What cities near Anaheim, CA are hiring for Internship Machine Learning Engineer New Grad jobs?

Cities near Anaheim, CA with the most Internship Machine Learning Engineer New Grad job openings:

Internship Machine Learning Engineer New Grad jobs near you
Infographic showing various Internship Machine Learning Engineer New Grad job openings in Anaheim, CA as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $44,581 per year, or $21.4 per hour.

Machine Learning Engineer

Mach Industries

Huntington Beach, CA • On-site

$120K - $160K/yr

Full-time

Medical, Life, Retirement

Posted 25 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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