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Internship Edge Ai Machine Learning Jobs in Riverside, CA

Bespoke Labs

Machine Learning Engineer

Pomona, CA · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

FieldAI

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$110K - $152K/yr

FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field ... edge. • Enforce best practices in security, compliance, and maintainability. • Mentor and ...

Turion Space

Lead AI Engineer

Irvine, CA

$110K - $144K/yr

Design, develop, and deploy advanced AI models and algorithms, including machine learning, deep ... competitive edge. * Performance Optimization: Monitor and optimize the performance of AI models ...

TRL11, Inc.

Sr Algorithms/Video Engineer

Irvine, CA · On-site

$150K - $220K/yr

TRL11 is a venture backed deep tech / defence tech startup bringing cutting-edge video technology ... Stay up to date with the latest advancements in AI, machine learning, and computer vision, evaluate ...

Month2Month

AI Engineer

Irvine, CA · On-site

$80K - $100K/yr

Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field ... cutting-edge AI technologies. Collaborative & Communicative: Excellent problem-solving and ...

TRL11, Inc.

Jr Algorithms/Video Engineer

Irvine, CA

$80 - $150K/hr

TRL11 is a venture backed deep tech / defence tech startup bringing cutting-edge video technology ... Stay up to date with the latest advancements in AI, machine learning, and computer vision, evaluate ...

TRL11, Inc.

Jr Algorithms/Video Engineer

Irvine, CA · On-site

$80 - $150K/hr

TRL11 is a venture backed deep tech / defence tech startup bringing cutting-edge video technology ... Stay up to date with the latest advancements in AI, machine learning, and computer vision, evaluate ...

TRL11, Inc.

Jr Algorithms/Video Engineer

Irvine, CA · On-site

$80 - $150K/hr

TRL11 is a venture backed deep tech / defence tech startup bringing cutting-edge video technology ... Stay up to date with the latest advancements in AI, machine learning, and computer vision, evaluate ...

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All JobsEdge Ai Machine Learning JobsInternship Edge Ai Machine Learning JobsInternship Edge Ai Machine Learning Jobs in Riverside, CA

Internship Edge Ai Machine Learning information

See Riverside, CA salary details

$26.6K

$44.4K

$91.8K

How much do internship edge ai machine learning jobs pay per year?

As of Aug 19, 2026, the average yearly pay for internship edge ai machine learning in Riverside, CA is $44,426.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,900.00 and $48,000.00 per year, depending on experience, location, and employer.

What is an internship edge AI machine learning?

Internship Edge AI Machine Learning positions are entry-level roles designed for students or recent graduates who want hands-on experience working with artificial intelligence and machine learning technologies, especially those related to 'edge' computing. These internships focus on developing, optimizing, and deploying AI/ML models that run on edge devices such as smartphones, IoT devices, and embedded systems, rather than in the cloud. Interns typically assist in research, data preparation, model training, and software development while gaining industry-relevant skills. These roles are ideal for individuals interested in both hardware and software aspects of AI. The experience gained can be valuable for future careers in data science, machine learning engineering, or AI research.

What types of projects can I expect to work on during an internship in edge AI and machine learning?

As an intern in Edge AI and Machine Learning, you will likely work on projects that involve developing and optimizing machine learning models for deployment on edge devices such as smartphones, IoT sensors, or embedded systems. Typical tasks include data preprocessing, model training and evaluation, and implementing algorithms with resource constraints in mind. You may also collaborate with hardware engineers and software developers to ensure that your solutions run efficiently on limited hardware. This hands-on experience provides a strong foundation for understanding real-world AI deployment challenges and can open doors to more advanced roles in the future.

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

To thrive in an Internship Edge AI Machine Learning role, you need a solid background in computer science, mathematics, and machine learning concepts, typically supported by coursework or relevant projects. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or PyTorch), and cloud or edge computing platforms is highly valuable. Strong analytical thinking, problem-solving abilities, and effective teamwork skills help you adapt and contribute meaningfully in collaborative research and development environments. These competencies are crucial for innovating and deploying machine learning models on edge devices, ensuring impactful real-world AI solutions.

What is the difference between Internship Edge Ai Machine Learning vs Data Analyst?

AspectInternship Edge Ai Machine LearningData Analyst
Required CredentialsRelevant coursework, basic programming skills, possibly some certificationsDegree in statistics, mathematics, or related field; proficiency in data tools
Work EnvironmentInternship setting, collaborative teams, research-focusedOffice environment, data-driven decision-making teams
Employer & Industry UsageTech companies, startups, research institutionsBusiness, finance, healthcare, marketing sectors

Internship Edge Ai Machine Learning roles typically focus on foundational skills in AI and machine learning, often as entry-level or internship positions. Data Analysts work across various industries analyzing data to inform business decisions. While both roles involve working with data, AI internships emphasize machine learning models, whereas Data Analysts focus on data interpretation and reporting.

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What cities near Riverside, CA are hiring for Internship Edge Ai Machine Learning jobs?

Cities near Riverside, CA with the most Internship Edge Ai Machine Learning job openings:

Internship Edge Ai Machine Learning jobs near you
Infographic showing various Internship Edge Ai Machine Learning job openings in Riverside, CA as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $44,426 per year, or $21.4 per hour.

Machine Learning Engineer

Bespoke Labs

Pomona, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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