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Temporary Machine Learning Engineer Jobs in Tulsa, OK

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 ...

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 ...

Summary We're looking for a Machine Learning Engineer to design, deploy, and operate production ML systems on Amazon Web Services. You'll own the full lifecycle in a real-world, high-stakes ...

Summary We're looking for a Machine Learning Engineer to design, deploy, and operate production ML systems on Amazon Web Services. You'll own the full lifecycle in a real-world, high-stakes ...

Summary We're looking for a Machine Learning Engineer to design, deploy, and operate production ML systems on Amazon Web Services. You'll own the full lifecycle in a real-world, high-stakes ...

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Showing results 1-20

Temporary Machine Learning Engineer information

See Tulsa, OK salary details

$28.8K

$117.6K

$176.7K

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

As of Jul 4, 2026, the average yearly pay for temporary machine learning engineer in Tulsa, OK is $117,614.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,700.00 and $141,600.00 per year, depending on experience, location, and employer.

What is the difference between Temporary Machine Learning Engineer vs Data Scientist?

AspectTemporary Machine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related fields; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentProject-based, often contract roles in tech or finance companiesResearch and analysis-focused, in tech, finance, or healthcare sectors
Employer UsageUsed for short-term ML projects, model deployment, or prototypingUsed for data analysis, insights, and predictive modeling

Temporary Machine Learning Engineers focus on implementing and deploying ML models on a short-term basis, often within project deadlines. Data Scientists analyze data to generate insights and develop models but may have a broader scope. Both roles require strong technical skills, but their primary functions differ in scope and application.

What are the most commonly searched types of Machine Learning Engineer jobs in Tulsa, OK? The most popular types of Machine Learning Engineer jobs in Tulsa, OK are:
What are popular job titles related to Temporary Machine Learning Engineer jobs in Tulsa, OK? For Temporary Machine Learning Engineer jobs in Tulsa, OK, the most frequently searched job titles are:
What job categories do people searching Temporary Machine Learning Engineer jobs in Tulsa, OK look for? The top searched job categories for Temporary Machine Learning Engineer jobs in Tulsa, OK are:
Infographic showing various Temporary Machine Learning Engineer job openings in Tulsa, OK as of June 2026, with employment types broken down into 81% Full Time, and 19% Contract. Highlights an 88% In-person, and 12% Remote job distribution, with an average salary of $117,614 per year, or $56.5 per hour.

Machine Learning Engineer

Bespoke Labs

Broken Arrow, OK โ€ข On-site

Full-time

Posted 17 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 โ€” 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 โ€” 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 โ€” SFT, RLHF, PPO, DPO, or reward model training โ€” 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 โ€” held-out sets, benchmark design, avoiding train/eval contamination