ZipRecruiter

Log In

1

Machine Learning Petroleum Engineer Jobs in Washington, DC

Beyond SOF

Engineer, Machine Learning

Washington, DC · On-site

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

Beyond SOF

Engineer, Machine Learning

Washington, DC · On-site

$120 - $160/hr

Role Summary The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties * Develop ...

THOMSON REUTERS

Machine Learning Engineer

Mclean, VA · On-site

Summary and Description We are seeking a Machine Learning Engineer to develop, operationalize, and improve machine learning systems that power a mission-driven investigative platform used by ...

Unissant

Machine Learning Engineer

Ashburn, VA · On-site

$110 - $170/hr

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA. The ideal candidate will bring hands‑on experience in machine learning, advanced analytics, and ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

Cymertek Corporation

Machine Learning Engineer

Reston, VA · On-site

$110 - $170/hr

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

next page

Showing results 1-20

All JobsMachine Learning Petroleum Engineer JobsMachine Learning Petroleum Engineer Jobs in Washington, DC

Machine Learning Petroleum Engineer information

See Washington, DC salary details

$35.7K

$145.8K

$219.2K

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

As of Aug 21, 2026, the average yearly pay for machine learning petroleum engineer in Washington, DC is $145,843.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,000.00 and $175,600.00 per year, depending on experience, location, and employer.

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 are the key skills and qualifications needed to thrive as a machine learning petroleum engineer?

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 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.

What are popular job titles related to Machine Learning Petroleum Engineer jobs in Washington, DC?

For Machine Learning Petroleum Engineer jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Machine Learning Petroleum Engineer jobs in Washington, DC look for?

The top searched job categories for Machine Learning Petroleum Engineer jobs in Washington, DC are:

Machine Learning Petroleum Engineer jobs near you

Engineer, Machine Learning

Beyond SOF

Washington, DC • On-site

Full-time

Re-posted 14 days ago

Job description

Role Summary:
The Machine Learning Engineer is
responsible for developing and
implementing machine learning models
and algorithms to solve complex
problems.
Main Responsibilities and Duties:
Develop and implement machine
learning models and algorithms.
Collaborate with the engineering team to
integrate machine learning solutions into
projects.
Stay updated on the latest machine
learning technologies and trends.
Develop and implement quantum
machine learning models and
algorithms. Collaborate with quantum
engineers to integrate quantum
machine learning solutions into the
company's projects.

Apply