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Machine Learning Petroleum Engineer Jobs (NOW HIRING)

Eccalon LLC

Machine Learning Engineer

Detroit, MI · On-site

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Spotify

Machine Learning Engineer

They are seeking a Machine Learning Engineer to build systems that analyze the performance of music promotions, providing actionable insights for creators and partners. Responsibilities : • ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

About the Position Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience. You ...

Corning

As a Machine Learning Engineer, you will work within a collaborative technical team to build, deploy, monitor, and maintain machine learning solutions that create measurable business value. You will ...

New

Spotify

Machine Learning Engineer

Spotify is a leading music streaming platform, and they are seeking a Machine Learning Engineer to join their Music Promotion team. The role involves building systems to understand the performance of ...

Jane Street

Machine Learning Engineer

New York, NY

About the Position Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience. You ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

... engineering/science, and a minimum of 3 years relevant industry experience Experience with software coding in Python. Experience with one of the following: machine learning/deep learning systems ...

Pattern AI

Machine Learning Engineer

San Mateo, CA

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 ...

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 ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site

As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive meaningful business outcomes at scale. You will work cross-functionally to bring innovative machine ...

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... machine learning models and algorithms that will improve Confie's business outcome/customer experience Perform data cleansing, analysis, and feature engineering using Python Ability to work with ...

Ksb

Machine Learning Engineer

Grovetown, GA · On-site

Machine Learning Engineer KSB GIW, Inc. Department: Engineering, Research & Development Reports to: Metallurgical and Materials R&D Lab Manager Location: Grovetown, GA, USA (onsite) Shift: First FLSA ...

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Machine Learning Petroleum Engineer information

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$31.5K

$128.8K

$193.5K

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

As of Jul 16, 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.

Will AI take over petroleum engineering jobs?

AI can automate certain tasks in petroleum engineering, such as data analysis and reservoir modeling, but it is unlikely to fully replace engineers. Human expertise remains essential for decision-making, problem-solving, and overseeing complex operations. Petroleum engineers will need to adapt by developing skills in AI tools and data management.

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.

Do ML engineers get paid well?

Machine Learning engineers typically earn high salaries due to their specialized skills in AI, data analysis, and programming. Salaries vary based on experience, location, and industry, but they are generally above average compared to other engineering roles.

What engineers make $500,000 a year?

Highly experienced senior engineers in specialized fields such as petroleum engineering, software engineering, or data science can earn $500,000 or more annually, especially with bonuses, stock options, or in leadership roles. Achieving this level typically requires advanced skills, extensive experience, and working in high-paying industries or companies.

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 engineers make $300,000 a year?

Senior petroleum engineers, especially those with extensive experience, specialized skills, and leadership roles, can earn $300,000 or more annually. Machine learning petroleum engineers working in the oil and gas industry with advanced expertise and in high-paying companies may also reach this salary level, often supplemented by bonuses and profit sharing.

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.
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 July 2026, with employment types broken down into 95% Full Time, 2% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.
Machine Learning Engineer

Machine Learning Engineer

Eccalon LLC

Detroit, MI • On-site

Full-time

Re-posted 23 days ago

Job description

Machine Learning Engineer

Location: Detroit, MI- Onsite

Type: Full-time

Security Clearance: No clearance required, must be clearable.

Job Description

The Machine Learning Engineer will be an essential member of the Research and Development Team, where we engineer large tailor-made systems to solve complex data-related problems from many domains. At Eccalon, the projects we support often require solutions that utilize the latest and the best from Deep Learning/Machine Learning research. We support advanced projects in both data constrained and data rich settings. Qualified candidates should be driven and be able to help craft these systems as a part of our R&D team.

Responsibilities

  • Candidates are expected to be familiar with the motions of a classical Machine Learning workflow, and support the team with some of the following tasks:
    • Dataset Creation.
    • Data Exploration/Visualization.
    • Literature Review.
    • Data Wrangling.
    • Implementation and Training of Appropriate Models from Literature.
    • Characterization of Error in Models.
    • Iterative Optimization of Models.
  • On the engineering side of development, the Machine Learning Engineer will have the ability to be hands-on by:
    • Creating training and preprocessing pipelines for faster experimentation.
    • Creating algorithmic modules to interface your Models output with business requirements.
    • Integrating their code to a larger codebase.
    • Putting your model into production using AWS or GCP.

Required Qualifications

  • BS. in Computer Science, or related field.
  • 3+ years of professional Software Development experience in Python.
  • Mastery of Deep Learning fundamentals and statistics underlying Machine Learning.
  • History of software projects putting Machine Learning systems into production in any capacity.
  • History of software projects in general.
  • Deep personal interest with the complete state of the art in a subfield of Machine Learning Research.
  • Ability to work independently, and within a team.
  • Ability to communicate effectively with non-technical stakeholders and supervisors.
  • Prior project experience combining two or more of the following in a production setting:
    • Unsupervised or Semi-supervised Learning.
    • Convolutional Architectures.
    • Autoencoders.
    • Recurrent Architectures for Time-Series Applications.
    • Transformer Architectures for Natural Language Processing.
    • Generative Adversarial Architectures.

Preferred qualifications

  • MS. or PhD in Machine Learning, or related field
  • Extensive AWS or GCP experience putting scalable Machine Learning systems into production.
  • Experience working with extremely high volume / high throughput data in a data lake / data warehousing / training / production environment.
  • Has implemented cutting edge methods (e.g. a custom layer) from recent Machine Learning publications / conference proceedings and has done so in PyTorch or Tensorflow.
  • Publications in AI/ML journals or conferences.

Equal Employment Opportunity (EEO) Policy

Eccalon provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

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About Eccalon

Sourced by ZipRecruiter

We are a cross-functional collective of innovative minds that leverages technology to tackle the most challenging problems of this generation for clients, the nation, and the world. Eccalon fosters creativity, curiosity, and imagination across all departments and divisions to pioneer new ideas, products, and services. We advance innovation.​

Industry

Guided missile and space vehicle manufacturing

Company size

11 - 50 Employees

Headquarters location

Hanover, MD, US

Year founded

2017

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