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Machine Learning Researcher Jobs in Oklahoma (NOW HIRING)

Read eval signal and training curves to determine whether a change actually helped, and feed findings back to the research and environment teams * Integrate RL environments into the training stack ...

Read eval signal and training curves to determine whether a change actually helped, and feed findings back to the research and environment teams * Integrate RL environments into the training stack ...

Read eval signal and training curves to determine whether a change actually helped, and feed findings back to the research and environment teams * Integrate RL environments into the training stack ...

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Showing results 21-40

Machine Learning Researcher information

See Oklahoma salary details

$27.7K

$104.4K

$151.9K

How much do machine learning researcher jobs pay per year?

As of Sep 4, 2026, the average yearly pay for machine learning researcher in Oklahoma is $104,431.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,900.00 and $142,200.00 per year, depending on experience, location, and employer.

What does a machine learning researcher do?

A Machine Learning Researcher designs, develops, and tests algorithms and models that allow computers to learn from and make decisions based on data. They often work on advancing the field by exploring new methods, improving existing algorithms, and publishing their findings. These researchers collaborate with engineers and data scientists to apply their research to practical problems in areas like computer vision, natural language processing, and robotics. Their work typically involves a combination of mathematics, statistics, programming, and experimentation.

What are the key skills and qualifications needed to thrive as a machine learning researcher?

To thrive as a Machine Learning Researcher, you need deep expertise in mathematics, statistics, programming (typically Python), and a strong academic background in computer science or related fields. Familiarity with frameworks like TensorFlow or PyTorch and experience with tools for data analysis and model development are standard, often supported by advanced degrees or relevant certifications. Critical thinking, creativity, and effective communication are vital soft skills for developing novel solutions and collaborating across interdisciplinary teams. These skills enable researchers to design innovative algorithms, validate models rigorously, and contribute impactful advancements in the field.

What are some common challenges machine learning researchers face when transitioning from academic research to industry roles?

Machine Learning Researchers often find that transitioning to industry involves adapting to faster project timelines, collaborative workflows, and a focus on scalable, real-world solutions rather than theoretical advances alone. In industry, you'll likely work closely with cross-functional teams, such as software engineers and product managers, to ensure models are both practical and maintainable. Balancing innovation with business objectives, handling production constraints, and communicating complex findings to non-technical stakeholders are some of the key challenges you may encounter.

What is the difference between Machine Learning Researcher vs Data Scientist?

AspectMachine Learning ResearcherData Scientist
Required CredentialsAdvanced degrees in CS, ML, or related fields; research experienceDegree in CS, statistics, or related; strong analytical skills
Work EnvironmentResearch labs, academia, R&D departmentsBusiness environments, tech companies, consulting
Employer & Industry UsageUniversities, research institutions, tech firmsCorporations, startups, finance, healthcare
Common Search & ComparisonFocus on theoretical ML advancementsFocus on data analysis & business insights

While both roles involve working with data and algorithms, Machine Learning Researchers primarily focus on developing new algorithms and advancing ML theory, often in research or academic settings. Data Scientists apply these techniques to analyze data, generate insights, and support business decisions in industry environments.

What are popular job titles related to Machine Learning Researcher jobs in Oklahoma?

For Machine Learning Researcher jobs in Oklahoma, the most frequently searched job titles are:

Infographic showing various Machine Learning Researcher job openings in Oklahoma as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $104,431 per year, or $50.2 per hour.

Machine Learning Engineer

Bespoke Labs

Oklahoma City, OK โ€ข On-site

Full-time

Re-posted 19 days ago


Job description

  • Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch

  • Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment orchestration

  • Run and scale training experiments on cloud or HPC (AWS, GCP, SLURM, Ray), and debug throughput, stability, and convergence issues

  • Build evaluation harnesses and benchmark infrastructure, with held-out sets and contamination controls, so results are trustworthy

  • Read eval signal and training curves to determine whether a change actually helped, and feed findings back to the research and environment teams

  • Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics

  • Implement methods from recent ML papers quickly and turn them into production-grade systems