ZipRecruiter

Log In

1

Machine Learning Petroleum Engineer Jobs in Baltimore, MD

Varsity Tutors

Machine Learning Tutor

College Park, MD · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Laurel, MD · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Baltimore, MD · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Bowie, MD · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

previous page

Showing results 41-60

All JobsMachine Learning Petroleum Engineer JobsMachine Learning Petroleum Engineer Jobs in Baltimore, MD

Machine Learning Petroleum Engineer information

See Baltimore, MD salary details

$31.3K

$128K

$192.3K

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

As of Aug 13, 2026, the average yearly pay for machine learning petroleum engineer in Baltimore, MD is $127,950.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,900.00 and $154,000.00 per year, depending on experience, location, and employer.

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 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.

What are popular job titles related to Machine Learning Petroleum Engineer jobs in Baltimore, MD?

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

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

The top searched job categories for Machine Learning Petroleum Engineer jobs in Baltimore, MD are:

What cities near Baltimore, MD are hiring for Machine Learning Petroleum Engineer jobs?

Cities near Baltimore, MD with the most Machine Learning Petroleum Engineer job openings:

Machine Learning Petroleum Engineer jobs near you

Artificial Intelligence/Machine Learning Engineer, Junior

EverWatch

Annapolis Junction, MD • On-site

Full-time

Re-posted 16 days ago

Job description

Job Summary:
EverWatch is a government solutions company providing advanced defense, intelligence, and deployed support to our country’s most critical missions. The AI/ML Engineer will develop and deploy artificial intelligence and machine learning solutions to enhance operational workflows and support decision-making in secure environments.
Responsibilities:
• Cyber and intelligence analysts rely on multi-step workflows that are time-sensitive, detail-rich, and critical to national security.
• As an AI/ML Engineer at EverWatch Solutions, you will work directly with mission users to develop and deploy artificial intelligence and machine learning solutions that enhance operational workflows, improve data accessibility, and support rapid decision-making in secure environments.
• You will collaborate with operators, analysts, software developers, and mission leadership to capture operational needs and translate them into effective AI-enabled capabilities.
• Your work may include developing LLM-powered workflows, agent-based automation, and other AI/ML solutions that streamline analytical tasks and improve mission effectiveness.
• You will support the integration of AI capabilities into existing operational systems while ensuring solutions are reliable, scalable, and compliant with security and governance requirements in classified environments.
• Additionally, you will contribute to data pipeline development, model evaluation, workflow optimization, and operational testing to support production-ready AI solutions.
Qualifications:
Required:
• 1-4 years of experience with Python for data analysis and machine learning tasks through academic, internship, or project-based work
• Knowledge of machine learning concepts including supervised learning, model evaluation, and data preprocessing
• Familiarity with standard data science libraries and development tools
• Ability to think analytically, solve problems effectively, and learn quickly in a fast-paced, mission-oriented environment
• Ability to collaborate within a team and communicate technical concepts clearly
• TS/SCI clearance with a polygraph
• Bachelor’s degree in computer science, Data Science, Electrical Engineering, Mathematics, Statistics, or a related technical field or master’s degree with limited experience
Preferred:
• Experience with academic coursework, thesis work, or capstone projects involving machine learning, natural language processing, or data science applications
• Experience with version control tools such as Git and collaborative development environments
• Knowledge of deep learning frameworks such as PyTorch or TensorFlow
• Knowledge of large language models (LLMs) and generative AI concepts
• Knowledge of cloud platforms such as AWS, Azure, or GCP
• Knowledge of containerization technologies such as Docker or Kubernetes
• Knowledge of agentic AI, retrieval-augmented generation (RAG), or other applied NLP techniques
• Prior internship, co-op, research, or project experience supporting government, defense, or intelligence community environments
Company:
EverWatch focuses on in-house investment management. Founded in 1999, the company is headquartered in West Palm Beach, USA, with a team of 201-500 employees. The company is currently Growth Stage.

Apply