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Contract Apple Machine Learning Engineer Jobs in Three Rivers, MI

Bespoke Labs

Machine Learning Engineer

Kalamazoo, MI · 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 ...

Varsity Tutors

Machine Learning Tutor

Kalamazoo, MI · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

Epic

Software Engineer

Kalamazoo, MI · On-site

... and machine learning tools to drive innovation in healthcare. • Invent better ways to reduce ... Engineering, Computer Engineering, or a related field • A history of academic excellence or ...

Varsity Tutors

Data Science Tutor

Kalamazoo, MI · Remote

$40/hr

... machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

Varsity Tutors

Python Tutor

Kalamazoo, MI · Remote

$40/hr

... Python to machine learning, web scraping, scientific computing, and DevOps applications ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

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Contract Apple Machine Learning Engineer information

See Three Rivers, MI salary details

$29.1K

$118.8K

$178.5K

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

As of Jun 23, 2026, the average yearly pay for contract apple machine learning engineer in Three Rivers, MI is $118,760.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,600.00 and $143,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Contract Apple Machine Learning Engineer, and why are they important?

To thrive as a Contract Apple Machine Learning Engineer, you need a strong background in computer science, mathematics, and deep learning, typically with a relevant degree and experience in building ML models. Proficiency with Python, TensorFlow or PyTorch, Apple's Core ML framework, and version control systems is commonly required. Strong problem-solving skills, collaboration, and effective communication help you navigate project requirements and work with cross-functional teams. These skills and experiences are crucial for delivering high-quality, scalable machine learning solutions that align with Apple's standards and rapidly evolving technology needs.

What are the common challenges faced by Contract Apple Machine Learning Engineers when integrating ML models into Apple’s ecosystem?

Contract Apple Machine Learning Engineers often encounter challenges such as ensuring seamless integration of machine learning models with Apple’s proprietary platforms like iOS, macOS, or Core ML. Adapting to Apple’s strict security, privacy standards, and performance requirements is essential, as is optimizing models for real-time performance on Apple devices. Collaborating effectively with cross-functional teams—such as software developers, designers, and QA engineers—is crucial to deliver scalable and user-friendly ML features within project timelines.

What are Contract Apple Machine Learning Engineers?

Contract Apple Machine Learning Engineers are professionals hired on a temporary or project basis to develop and implement machine learning models and algorithms specifically for Apple’s products and platforms. They typically work on tasks such as optimizing machine learning workflows for iOS, macOS, or other Apple technologies, and may collaborate closely with Apple’s in-house teams. Their responsibilities can include data preprocessing, model training, evaluation, and integration into Apple’s ecosystem. These engineers are expected to have expertise in machine learning frameworks, programming languages like Python or Swift, and a strong understanding of Apple’s development tools. Contract roles often provide flexibility but may require quick adaptation to Apple’s proprietary systems and high standards.
What cities near Three Rivers, MI are hiring for Contract Apple Machine Learning Engineer jobs? Cities near Three Rivers, MI with the most Contract Apple Machine Learning Engineer job openings:
Contract Apple Machine Learning Engineer jobs near you

Machine Learning Engineer

Bespoke Labs

Kalamazoo, MI • 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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