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Junior Machine Learning Engineer Jobs in Oklahoma

Pwc

AI Engineer

Tulsa, OK · On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Building ...

Pwc

US Tech - AI Engineering Manager

Tulsa, OK · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... Responsibilities - Mentor junior engineers and foster their growth - Maintain security and ...

Pwc

US Tech - AI Engineering Manager

Oklahoma City, OK

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... Responsibilities - Mentor junior engineers and foster their growth - Maintain security and ...

Camgian

Senior Software Engineer

Lawton, OK · On-site

$90 - $130/hr

Production deployment of Machine Learning (ML) models Responsibilities ... Train & mentor junior engineers, performarchitecture,designandcode reviews * Leadcontinuous process ...

New

Camgian Corporation

Senior Software Engineer

Lawton, OK · On-site

$120K - $158K/yr

Production deployment of Machine Learning (ML) models Responsibilities * Lead software development ... Train & mentor junior engineers, perform architecture, design and code reviews * Lead continuous ...

Camgian Corporation

Senior Software Engineer

Lawton, OK · On-site

$120K - $158K/yr

Production deployment of Machine Learning (ML) models Responsibilities * Lead software development ... Train & mentor junior engineers, perform architecture, design and code reviews * Lead continuous ...

Accenture

Collaborate with data engineers, software engineers, machine learning engineers, architects, cybersecurity specialists, and platform teams to operationalize scalable AI solutions using MLOps ...

Accenture

Senior Data Scientist

Oklahoma City, OK · On-site

Collaborate with data engineers, software engineers, machine learning engineers, architects, cybersecurity specialists, and platform teams to operationalize scalable AI solutions using MLOps ...

Camgian Corporation

Senior AI Engineer

Lawton, OK · On-site

$100 - $130/hr

We are focused on applying state-of-the-art Artificial Intelligence, Machine Learning, Computer ... Provide mentorship and guidance to junior engineers * Track project/product milestones and releases ...

Camgian Corporation

Senior AI Engineer

Lawton, OK · On-site

$102K - $141K/yr

We are focused on applying state-of-the-art Artificial Intelligence, Machine Learning, Computer ... Provide mentorship and guidance to junior engineers * Track project/product milestones and releases ...

Camgian Corporation

Senior AI Engineer

Lawton, OK · On-site

$102K - $141K/yr

We are focused on applying state-of-the-art Artificial Intelligence, Machine Learning, Computer ... Provide mentorship and guidance to junior engineers * Track project/product milestones and releases ...

Pwc

NGA AI Engineer Manager

Tulsa, OK · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Pwc

NGA AI Engineer Manager

Oklahoma City, OK · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Nebius

$91K - $119K/yr

The role We are seeking a highly skilled ML/AI Engineer to join our team to lead and support benchmarking of GPU platforms benchmarking of GPU platforms for machine learning and AI workloads. You ...

The OSU/A&M System

Post-Doctoral Fellow AF7770

Stillwater, OK · On-site

$46K - $62K/yr

Experience applying machine learning, system identification, reduced-order modeling, or advanced data-analysis methods to scientific or engineering problems. * Proficiency in scientific programming ...

New

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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Oklahoma

Junior Machine Learning Engineer information

See Oklahoma salary details

$30.9K

$66.3K

$101.1K

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

As of Aug 14, 2026, the average yearly pay for junior machine learning engineer in Oklahoma is $66,295.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,800.00 and $73,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer, and why are they important?

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

More about Junior Machine Learning Engineer jobs

What are the most commonly searched types of Machine Learning Engineer jobs in Oklahoma?

The most popular types of Machine Learning Engineer jobs in Oklahoma are:

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

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

What job categories do people searching Junior Machine Learning Engineer jobs in Oklahoma look for?

The top searched job categories for Junior Machine Learning Engineer jobs in Oklahoma are:

What cities in Oklahoma are hiring for Junior Machine Learning Engineer jobs?

Cities in Oklahoma with the most Junior Machine Learning Engineer job openings:

Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Oklahoma as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $66,295 per year, or $31.9 per hour.

Senior Engineer - Data Science

Continental Resources, Inc.

Oklahoma City, OK • On-site

Full-time

Re-posted 28 days ago

Job description

Job Summary
The Senior Engineer, Data Science is a hands-on technical role who designs, builds, and operationalizes advanced analytics and Artificial Intelligence/Machine Learning solutions that drive measurable value across subsurface, drilling and completions, production operations, HSE, and commercial functions at Continental Resources. This role partners with multidisciplinary stakeholders to translate business problems into data-driven solutions, develop robust models and pipelines, and deploy them to production with strong Machine Learning Ops and governance practices. The ideal candidate combines a Master of Science in Data Science with strong applied analytics capability, solid data engineering skills, and practical oil and gas domain experience comparable to a seasoned upstream engineering background.
Duties and Responsibilities
  • Leads the design, development, and deployment of Artificial Intelligence/Machine Learning solutions for upstream subsurface and well operations, including physics-informed and hybrid modeling approaches for reservoir, drilling, and production optimization.
  • Builds advanced Artificial Intelligence/Machine Learning solutions for commercial analytics use cases such as pricing, supply chain, marketing, and trading to improve profitability and decision speed.
  • Executes complex AI initiatives from ideation and discovery through model development, deployment, and sustainment as part of integrated, enterprise-level teams.
  • Architects and implements reliable data pipelines and features using modern data platforms (e.g., Databricks, cloud services), ensuring data quality, lineage, and performance for analytics workloads.
  • Applies Machine Learning Ops best practices to automate training, testing, deployment, monitoring, and model lifecycle management at scale in production environments.
  • Translates complex business problems into analytical approaches with clear hypotheses, success criteria, and measurable outcomes across upstream and commercial domains.
  • Develops and delivers communications that convey a clear understanding of technical concepts, model results, and business implications to diverse technical and non-technical audiences.
  • Builds strong partnerships and cross-functional relationships with geoscience, engineering, operations, commercial, IT, and leadership stakeholders to drive adoption and sustain business impact.
  • Gains the confidence and trust of others through honesty, integrity, and follow-through while championing responsible and secure use of data and AI.
  • Actively seeks new ways to grow and be challenged by staying current on emerging Artificial Intelligence/Machine Learning, generative AI, optimization, and computational techniques relevant to energy and integrating them where they add value.
  • Other duties as assigned.

Skills and Competencies
  • Collaborates - Building partnerships and working collaboratively with others to meet shared objectives.
  • Action oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
  • Drives results - Consistently achieving results, even under tough circumstances.
  • Self-development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
  • Nimble learning - Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder.
  • Situational adaptability - Adapting approach and demeanor in real time to match the shifting demands of different situations.
  • Instills trust - Gaining the confidence and trust of others through honesty, integrity, and authenticity.

Required Qualifications
  • Bachelor of Science in Petroleum, Mechanical, Chemical, or related Engineering discipline from an accredited college or university and Master of Science in Data Science, or a closely related data science or analytics field, from an accredited college or university.
  • Minimum five (5) years of hands-on experience delivering production-grade data science/Machine Learning solutions, including end-to-end lifecycle from discovery to deployment and sustainment.
  • Proficiency in Python and SQL; experience with Machine Learning frameworks and tooling (e.g., scikit-learn, PyTorch/TensorFlow), and data platforms such as Databricks and cloud services.
  • Experience building and maintaining data pipelines and features and applying Machine Learning Ops practices for model deployment and monitoring in enterprise environments.
  • Demonstrated ability to partner with technical and business domains in energy, including upstream subsurface, drilling/completions, production operations, and/or commercial analytics such as pricing, supply chain, marketing, or trading.
  • An acceptable pre-employment background and drug test.

Preferred Qualifications
  • Oil and gas industry experience, particularly in upstream engineering, subsurface, drilling and completions, production operations, or commercial energy analytics.
  • Background in computational sciences, optimization, or high-performance computing for engineering applications.
  • Familiarity with enterprise data governance, security, and responsible AI practices in regulated environments.
  • Five (5) or more years of combined oil and gas engineering/domain experience and applied data science experience.

Physical Requirements and Working Conditions
  • Requires prolonged sitting, some bending and stooping.
  • Occasional lifting up to 25 pounds.
  • Manual dexterity sufficient to operate a computer keyboard and calculator.

Continental Resources, Inc. provides equal employment opportunities and access for all applicants and employees without regard to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, national origin, age, disability, genetic information, veteran status, or any other category protected by law.

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