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Artificial Intelligence And Machine Learning Jobs in Oklahoma

SwiftCruit

Senior Engineer, Data Science

Oklahoma City, OK · On-site

$150 - $190/hr

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.

Instacart

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Instacart

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Instacart

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Robert Half

Senior AI Engineer

Oklahoma City, OK · On-site

$10K - $120K/yr

This includes intelligent agents, copilots, retrieval systems, and machine learning solutions. This is an exciting opportunity for someone who is passionate about artificial intelligence, curious ...

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How much do artificial intelligence and machine learning jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for artificial intelligence and machine learning in Oklahoma is $24.33, according to ZipRecruiter salary data. Most workers in this role earn between $19.76 and $25.77 per hour, depending on experience, location, and employer.

What jobs can I get with artificial intelligence and machine learning?

Jobs in artificial intelligence and machine learning include roles such as AI engineer, machine learning engineer, data scientist, research scientist, and AI software developer. These positions typically require skills in programming languages like Python or R, knowledge of algorithms, and experience with tools such as TensorFlow or PyTorch. They are found across industries including technology, finance, healthcare, and automotive sectors.

What are some common challenges faced by professionals working in artificial intelligence and machine learning roles?

Professionals in AI and Machine Learning often encounter challenges such as managing large datasets, ensuring data quality, and selecting the most appropriate algorithms for specific problems. Additionally, they must stay up-to-date with rapidly evolving technologies and frameworks, which requires continuous learning. Collaborating with cross-functional teams, such as data engineers and domain experts, is vital for translating business needs into effective AI solutions. Balancing project deadlines with the experimentation and iteration needed for model development can also be demanding.

What is artificial intelligence and machine learning?

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks typically requiring human intelligence, such as reasoning, problem-solving, and understanding language. Machine Learning (ML) is a subset of AI that focuses on creating algorithms and statistical models that enable computers to learn from data and improve their performance over time without being explicitly programmed. Together, AI and ML are used in a wide range of applications, from virtual assistants and recommendation systems to autonomous vehicles and medical diagnosis. These technologies are rapidly evolving and have a significant impact across many industries.

What are the key skills and qualifications needed to thrive as an artificial intelligence and machine learning engineer?

To thrive as an AI/ML Engineer, you need strong skills in mathematics, statistics, programming (Python, R), and a solid understanding of machine learning algorithms, typically supported by a degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and tools like scikit-learn, as well as experience with cloud platforms and relevant certifications, is highly valuable. Critical thinking, creativity, and effective communication help in solving complex problems and collaborating across interdisciplinary teams. These skills are crucial for developing robust AI solutions that drive innovation and deliver tangible business value.

Is artificial intelligence and machine learning a good career?

Artificial Intelligence and Machine Learning are rapidly growing fields with high demand for skilled professionals, offering competitive salaries and diverse opportunities across industries. Success typically requires strong programming skills, knowledge of algorithms, and experience with tools like Python and TensorFlow. It is considered a promising career path for those interested in technology and data analysis.
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Artificial Intelligence And Machine Learning jobs near you
Infographic showing various Artificial Intelligence And Machine Learning job openings in Oklahoma as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $50,602 per year, or $24.3 per hour.

Senior Engineer - Data Science

Continental Resources, Inc.

Oklahoma City, OK • On-site

Full-time

Re-posted 25 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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