ZipRecruiter

Log In

1

Machine Learning Petroleum Engineer Jobs (NOW HIRING)

Alignerr

Machine Learning Engineer

Seattle, WA · Remote

Machine Learning Engineer (AI Data Trainer) About the Role What if your expertise in machine learning could directly influence how the next generation of AI models reason, plan, and solve complex ...

Purple Drive

Machine Learning Engineer

Newark, NJ · On-site

Machine Learning Engineer As a Machine Learning Engineer , you will play a critical role in designing, developing, and deploying advanced machine learning solutions that drive innovation and create ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

... machine learning/deep learning systems, computer vision, graphics, computational imaging applications.Experience with Pytorch. MS/PhD in computer vision, electrical, optical or computer engineering ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

ManTech

Machine Learning Engineer

Herndon, VA · On-site

The Machine Learning Engineer will leverage their strong technical background and knowledge to support highly scalable machine learning-based applications, including both pipelines and services ...

k1x

Machine Learning Engineer

Manhattan, NY · Remote

As a Machine Learning Engineer, you will play a critical role in developing and implementing machine learning models that enhance our software's ability to accurately and efficiently process ...

ExtendMyTeam

Machine Learning Engineer

Austin, TX · On-site

Position Summary We are seeking a Machine Learning Engineer to help design, implement, and scale AI-enabled solutions that improve software delivery workflows, automate operational processes, and ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

LeanData

Machine Learning Engineer

Santa Clara, CA · On-site

Machine Learning Engineer LeanData helps the world's fastest-growing companies automate, simplify, and accelerate revenue. We are looking for a curious and innovative Machine Learning Engineer to ...

Steampunk

Machine Learning Engineer

Mclean, VA · On-site +1

$115K - $150K/yr

We are looking for a more than just a "Machine Learning Engineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

Steampunk

Machine Learning Engineer

Mclean, VA · On-site

$115K - $150K/yr

We are looking for seasoned Machine Learning Engineer to work with our existing team of Data Scientists and Engineers to use AI/ML technology in supporting Federal use cases. We are looking for a ...

next page

Showing results 1-20

People also search for

All JobsMachine Learning Petroleum Engineer Jobs

Machine Learning Petroleum Engineer information

See salary details

$31.5K

$128.8K

$193.5K

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

As of Jun 4, 2026, the average yearly pay for machine learning petroleum engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Petroleum Engineer, and why are they important?

To thrive as a Machine Learning Petroleum Engineer, you need a strong background in petroleum engineering, programming (such as Python or R), and applied machine learning, usually supported by a relevant engineering degree. Familiarity with data analysis platforms, machine learning frameworks (like TensorFlow or Scikit-learn), and petroleum industry software (such as Petrel or Eclipse) is essential. Strong analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for integrating technical insights with business goals. These competencies enable the effective application of data-driven solutions to optimize exploration, production, and operational efficiency in the energy sector.

How does a Machine Learning Petroleum Engineer typically collaborate with geoscientists and drilling teams to optimize oil and gas production?

A Machine Learning Petroleum Engineer works closely with geoscientists and drilling teams by integrating data-driven models into exploration and production workflows. They analyze geological, seismic, and operational data to develop predictive algorithms that identify optimal drilling locations, forecast reservoir performance, and improve recovery rates. Regular collaboration involves translating complex data insights into actionable recommendations that guide drilling strategies and inform real-time decisions, ensuring all teams are aligned to maximize efficiency and safety. This multidisciplinary approach fosters continuous learning and innovation across teams.

What is a Machine Learning Petroleum Engineer?

A Machine Learning Petroleum Engineer is a specialist who combines expertise in petroleum engineering with machine learning and data science techniques. They use advanced algorithms and data analytics to optimize oil and gas exploration, drilling, production, and reservoir management. Their work helps improve decision-making, reduce operational costs, and increase efficiency by analyzing large datasets from various sources such as sensors, seismic data, and production logs. These professionals often work closely with geoscientists, data engineers, and other stakeholders in the energy sector.

What is the difference between Machine Learning Petroleum Engineer vs Reservoir Engineer?

AspectMachine Learning Petroleum EngineerReservoir Engineer
Required CredentialsBachelor's/Master's in Petroleum Engineering, Data Science, or related fields; knowledge of machine learningBachelor's/Master's in Petroleum Engineering or Geosciences; strong understanding of reservoir simulation
Work EnvironmentData analysis, modeling, software development in oil & gas companiesReservoir modeling, field development planning in oil & gas operations
Industry UsageApplying machine learning to optimize extraction, predict reservoir behaviorEstimating reservoir properties, managing production strategies

The Machine Learning Petroleum Engineer focuses on integrating data science and machine learning techniques to optimize oil extraction processes, while the Reservoir Engineer specializes in modeling and managing subsurface reservoirs to maximize recovery. Both roles are vital in the oil & gas industry but differ in their core skills and daily tasks.

More about Machine Learning Petroleum Engineer jobs
What cities are hiring for Machine Learning Petroleum Engineer jobs? Cities with the most Machine Learning Petroleum Engineer job openings:
What states have the most Machine Learning Petroleum Engineer jobs? States with the most job openings for Machine Learning Petroleum Engineer jobs include:
What job categories do people searching Machine Learning Petroleum Engineer jobs look for? The top searched job categories for Machine Learning Petroleum Engineer jobs are:
Machine Learning Petroleum Engineer jobs near you
Infographic showing various Machine Learning Petroleum Engineer job openings in the United States as of May 2026, with employment types broken down into 7% Internship, 89% Full Time, and 4% Temporary. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

Waypoint Human Capital

Huntsville, AL • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Position Title: Machine Learning Engineer
Position Type: Full-time, On-Site
Location: Huntsville, AL
Clearance: Active TS
Description:
Waypoint's client is seeking a Machine Learning Engineer to support mission-critical efforts within a secure environment at the Missile and Space Intelligence Center. This role focuses on developing, integrating, and operationalizing machine learning solutions that support advanced analytics and intelligence capabilities.
The selected candidate will work across the full machine learning lifecycle, from building data pipelines and training models to deploying and monitoring production systems. This position requires a strong blend of software engineering and data science expertise, with a focus on scalability, performance, and system integration.
Responsibilities:
• Integrate machine learning systems into existing software architectures and enterprise platforms
• Design, build, and optimize data pipelines to support model training and inference
• Develop, test, and deploy machine learning models into production environments
• Manage transition from prototype to production, including deployment pipelines and monitoring solutions
• Monitor model performance, including handling model drift, rollback, and failure scenarios
• Conduct experiments and testing to evaluate and improve model accuracy and performance
• Write clean, maintainable, and testable code in Python and related technologies
• Collaborate with cross-functional teams to integrate ML capabilities into mission systems
• Utilize CI/CD pipelines and GitOps practices to support automated deployment and version control
• Support development in Linux and Windows environments
Required:
• Active TS clearance (with ability to obtain TS/SCI with CI Polygraph)
• Bachelor's degree in Computer Science, Mathematics, Statistics, Physics, or related technical field
• Minimum 12+ years of overall experience, including 1-3 years working with machine learning frameworks
• Strong programming skills in Python
• Experience with machine learning frameworks, libraries, and data modeling techniques
• Solid understanding of the machine learning lifecycle
• Experience working with SQL and NoSQL databases
• Experience working in Linux and Windows environments
• Familiarity with CI/CD pipelines and Agile development methodologies
• Understanding of software design and system integration principles
Desired:
• Active TS/SCI with CI Polygraph (desired)
• Experience working with large-scale (petabyte-level) datasets
• Experience supporting multi-INT analytics environments
• Experience deploying, monitoring, and scaling machine learning models in production
• Experience with tools such as Docker, Jupyter Notebooks, PostgreSQL, GitLab, and GitHub
• Experience implementing GitOps workflows
• Experience working in secure or classified environment

Apply