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Weekend Machine Learning Jobs in Tucson, AZ (NOW HIRING)

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 ...

Develop, validate, and deploy advanced statistical, machine learning, and deep learning predictive models to generate actionable insights for institutional and research stakeholders. * Design and ...

Senior Software Engineer I

Tucson, AZ

$115K - $152K/yr

Collaborate with researchers on artificial intelligence, machine learning, and computer vision. * Preform rapid prototyping and enhanced development to be integrated into operational systems.

Scientist

Tucson, AZ · On-site

$80K - $130K/yr

Experience with machine learning, deep learning, artificial intelligence, object classification, and/orautomated target recognition * Physics-based modeling and simulation experience * Experience ...

Incorporates machine learning (including large language models/LLMs) into scalable applications, owns data/model pipelines end-to-end, and partners with product, security, and platform teams to ...

AI Developer

Marana, AZ · On-site

$111K - $130K/yr

Incorporates machine learning (including large language models/LLMs) into scalable applications, owns data/model pipelines end-to-end, and partners with product, security, and platform teams to ...

Directly engage in restocking vending machines, VMI cabinets, and toolcribs, ensuring that ... Continuous Learning : Stay updated with the latest inventory management tools, techniques, and best ...

Steward (Vahi Taa'am)

Tucson, AZ · On-site

$12.25 - $16.75/hr

Utilizes dish machines and other equipment ensuring safety and cautionary signage are appropriately ... Participates in cross-training, as available, such as learning how to prep food items. * Works ...

Career Growth & Learning - 40% of our management hires are internal promotions! * Invest in Your ... Sort laundry, operate machines safely, and handle linen like it's made of gold (or at least 600 ...

Career Growth & Learning - 40% of our management hires are internal promotions! * Invest in Your ... Sort laundry, operate machines safely, and handle linen like it's made of gold (or at least 600 ...

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Weekend Machine Learning information

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Infographic showing various Weekend Machine Learning job openings in Tucson, AZ as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer

Bespoke Labs

Tucson, AZ • On-site

Full-time

Re-posted 12 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