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Machine Learning Petroleum Engineer Jobs in Washington, DC

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 AI ...

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 ...

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

About the Role We are seeking a Machine Learning Engineer to design, build, and evaluate advanced machine learning systems across AI safety and model evaluation applications. This role combines ...

Machine Learning Engineer

Mclean, VA · On-site

$105K - $115K/yr

As a Machine Learning Engineer at Somatus, you will work collaboratively with our data and technology teams to help clinical, operational, and financial partners solve advanced analytical problems.

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

Machine Learning Engineer The Opportunity: As an experienced AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct ...

Showing results 21-40

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 Engineer

UNISSANT

Ashburn, VA

Full-time

Posted 17 days ago


Job description

Unissant, Inc. delivers innovative capabilities to the agencies that keep our nation healthy and safe. We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results for our clients. Working collaboratively, we advance missions and careers through a focus on honesty, integrity, and dependability. We continuously look for talent, excited to join that effort. To learn more about our exciting organization, please visit us at www.unissant.com.

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 AI-driven product development, with the ability to turn complex data into practical, mission-focused solutions. This role is well suited for a technically strong professional who enjoys building and improving models, partnering across Agile teams, and supporting the delivery of innovative capabilities from early concept through deployment and ongoing performance optimization.

Essential Duties and Responsibilities:

  • Design, develop, and maintain machine learning models that support a variety of AI applications.
  • Analyze large and complex datasets to identify trends, test hypotheses, and generate actionable insights using statistical and analytical methods.
  • Build and support reliable data pipelines that improve data quality, accessibility, and usability for machine learning and analytics initiatives.
  • Collaborate with data engineering and cross-functional teams to enhance data workflows and optimize supporting infrastructure.
  • Contribute to AI product development activities across the lifecycle, including prototyping, implementation, deployment, and post-production support.
  • Monitor model effectiveness and product performance metrics, and perform ongoing enhancements to improve accuracy, scalability, and reliability.
  • Work closely with product managers, developers, designers, and QA teams within a large Agile development environment.

Work Experience and Job Skills:

  • Three (3) to four (4) years of hands-on experience in machine learning engineering, AI solution development, data analytics, or related technical work is preferred.
  • Experience supporting AI, machine learning, or advanced analytics initiatives is required.
  • Demonstrated experience developing and deploying AI/ML models in a production environment.
  • Proficiency in Python, R, Java, or similar programming languages used for machine learning and analytics development.
  • Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Familiarity with MLOps practices, CI/CD pipelines, and model deployment processes.
  • Working knowledge of SQL and NoSQL databases and data processing tools such as Apache Spark or Hadoop.
  • Experience with analytics and visualization tools such as Tableau, Power BI, matplotlib, or Plotly.
  • Exposure to cloud platforms such as AWS, Azure, or GCP for model deployment, storage, or related services is preferred.
  • Strong problem-solving abilities, attention to detail, and organizational skills.
  • Ability to manage multiple assignments independently while collaborating effectively across technical and business teams.
  • Experience working in Agile product development environments is a plus.

Education:

  • Bachelor's Degree in Computer Science, Data Science, Electrical Engineering, Physics, or a related technical field is required.
  • Master's Degree in a relevant field is preferred.
  • Equivalent combination of education and experience may be considered in lieu of strict degree requirements, based on client standards.

Certificates, Licenses and Registrations:

  • Relevant certifications in cloud computing, machine learning, data science, or data engineering are a plus.
  • Additional technical certifications may be considered based on program requirements.

Communication Skills:

  • Excellent verbal and written communication skills, with the ability to clearly explain technical concepts to both technical and non-technical audiences.
  • Strong interpersonal skills and the ability to collaborate effectively across cross-functional teams in a client-facing environment.

Clearance Requirements:

  • Ability to obtain and maintain a Public Trust position and favorable suitability determination based on a CBP background investigation is required.

Travel:

  • This is a hybrid position based in Ashburn, VA, with onsite support expected one to two days per week and additional onsite presence as required by mission needs.

Environmental Requirements:

  • Mainly a routine office environment.
  • May be required to lift up to ten (10) pounds.
  • Flexible in working extended hours.

The above statements are intended to describe the general nature and level of work being performed by the individual(s) assigned to this position. They are not intended to be an exhaustive list of all duties, responsibilities, and skills required. Unissant management reserves the right to modify, add, or remove duties and to assign other duties as necessary. In addition, where applicable and available, reasonable accommodation(s) may be made to enable individuals with disabilities to perform essential functions of this position.

Please note: Candidate(s) will be required to go through pre-employment screening.

Unissant, Inc. is a proud Equal Opportunity Employer! (EOE; M/F/Disability/Vets)