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Machine Learning Engineer Starting Jobs in Kalamazoo, 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

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

WSI Talent

Machine Operator

Sturgis, MI · On-site

$17/hr

Through scientific molding technologies and superior in-house tool engineering, this plastic ... Starting pay of $ 17 an hour * Weekly pay * Entry-level positions (no work experience or diploma ...

Varsity Tutors

Data Science Tutor

Kalamazoo, MI · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Varsity Tutors

Python Tutor

Kalamazoo, MI · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

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Machine Learning Engineer Starting information

See Kalamazoo, MI salary details

$29.8K

$122K

$183.3K

How much do machine learning engineer starting jobs pay per year?

As of Aug 13, 2026, the average yearly pay for machine learning engineer starting in Kalamazoo, MI is $121,998.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,200.00 and $146,800.00 per year, depending on experience, location, and employer.

What are entry-level machine learning engineer jobs?

Entry-level machine learning engineer jobs typically involve developing and testing machine learning models, often requiring knowledge of programming languages like Python and familiarity with frameworks such as TensorFlow or PyTorch. These roles usually require a bachelor's degree in computer science, data science, or related fields, and may include tasks like data preprocessing, model evaluation, and collaboration with data teams.
What cities near Kalamazoo, MI are hiring for Machine Learning Engineer Starting jobs? Cities near Kalamazoo, MI with the most Machine Learning Engineer Starting job openings:
Machine Learning Engineer Starting jobs near you
Infographic showing various Machine Learning Engineer Starting job openings in Kalamazoo, MI as of August 2026, with employment types broken down into 82% Full Time, 9% Contract, and 9% Nights. Highlights an 100% In-person job distribution, with an average salary of $121,842 per year, or $58.6 per hour.

Machine Learning Engineer

Bespoke Labs

Kalamazoo, MI • On-site

Full-time

Re-posted 26 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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