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Machine Learning Petroleum Engineer Jobs in Austin, TX

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

* Develop high-quality, maintainable code to build and deploy computer vision modules and machine learning models as part of an AI pipeline * Works with data and software engineering team to integrate ...

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

* Develop high-quality, maintainable code to build and deploy computer vision modules and machine learning models as part of an AI pipeline * Works with data and software engineering team to integrate ...

Roku

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

We're looking for seasoned engineers with a background in machine learning to aid in this mission. Examples of problems include improving ad relevance, inferring demographics, yield optimization, and ...

TalentPros.AI

Staff Machine Learning Engineer

Austin, TX · On-site

$120K - $550K/yr

We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll transform groundbreaking research into real-world applications that can change industries, enhance ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

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Showing results 21-40

All JobsMachine Learning Petroleum Engineer JobsMachine Learning Petroleum Engineer Jobs in Austin, TX

Machine Learning Petroleum Engineer information

See Austin, TX salary details

$31.2K

$127.6K

$191.8K

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

As of Aug 25, 2026, the average yearly pay for machine learning petroleum engineer in Austin, TX is $127,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $153,600.00 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 Austin, TX?

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

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

The top searched job categories for Machine Learning Petroleum Engineer jobs in Austin, TX are:

What cities near Austin, TX are hiring for Machine Learning Petroleum Engineer jobs?

Cities near Austin, TX with the most Machine Learning Petroleum Engineer job openings:

Machine Learning Petroleum Engineer jobs near you
Infographic showing various Machine Learning Petroleum Engineer job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $127,637 per year, or $61.4 per hour.

Machine Learning Engineer L-1

Austin, TX • On-site

Lauretta AI LLC
See more jobs at Lauretta AI LLCexternal

$80K - $93K/yr

Full-time

Re-posted 28 days ago

Job description

Job Description:
  • Develop high-quality, maintainable code to build and deploy computer vision modules and machine learning models as part of an AI pipeline
  • Works with data and software engineering team to integrate models into pipeline
  • Support construction and iteration of product prototypes
  • Support data pipeline engineering and automation
  • Stay up to date with state of the art developments in computer vision tasks
  • Other duties as required by supervisors
Additional Requirements:
  • Due to government contract requirements, applicants are able to get clearance are preferred
  • Experience working in MLOps and building pipelines for deploying ML models
  • Programming skills in Python, C/C++ or Javascript
  • Understanding of machine learning and deep learning fundamentals
  • Develop internal tooling as needed to support ML efforts
  • Production deployment and performance monitoring including code refactoring and optimization as needed
  • Support infrastructure engineering, security engineering, and architecture
  • Willing to learn and work well in a cross functional team environment
  • Fresh graduates are welcome to apply on a full-time basis