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Internship Apple Machine Learning Engineer Jobs in Chicago, IL

Bespoke Labs

Machine Learning Engineer

Gary, IN · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Hammond, IN · On-site

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 ...

Lightspeed

AI & Machine Learning Engineer

Northbrook, IL · On-site

$100 - $130/hr

As an AI & Machine Learning Engineer, you will design, build, and deploy the intelligent systems that make LightSpeed's construction robots smarter, faster, and more autonomous. You will develop ...

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All JobsApple Machine Learning Engineer JobsInternship Apple Machine Learning Engineer JobsInternship Apple Machine Learning Engineer Jobs in Chicago, IL

Internship Apple Machine Learning Engineer information

See Chicago, IL salary details

$26.3K

$43.9K

$90.7K

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

As of Aug 9, 2026, the average yearly pay for internship apple machine learning engineer in Chicago, IL is $43,867.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,500.00 and $47,400.00 per year, depending on experience, location, and employer.

What is the difference between Internship Apple Machine Learning Engineer vs Software Engineering Intern?

AspectInternship Apple Machine Learning EngineerSoftware Engineering Intern
Required CredentialsRelevant coursework, programming skills, some experience in MLComputer science fundamentals, programming skills, coursework
Work EnvironmentResearch-focused, data-driven projects within AppleSoftware development projects, coding, testing
Employer & Industry UsageApple, technology, AI/ML applicationsVarious tech companies, software development

Both roles involve programming and technical skills, but the Internship Apple Machine Learning Engineer focuses on machine learning projects within Apple, requiring knowledge of ML frameworks. The Software Engineering Intern role is broader, emphasizing general software development. Candidates interested in AI/ML should consider the Machine Learning Engineer internship for specialized experience, while those seeking general software development roles may prefer the Software Engineering Intern position.

What are popular job titles related to Internship Apple Machine Learning Engineer jobs in Chicago, IL? For Internship Apple Machine Learning Engineer jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Internship Apple Machine Learning Engineer jobs in Chicago, IL look for? The top searched job categories for Internship Apple Machine Learning Engineer jobs in Chicago, IL are:
Internship Apple Machine Learning Engineer jobs near you

Machine Learning Engineer

Bespoke Labs

Gary, IN • On-site

Full-time

Re-posted 23 days ago

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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