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Machine Learning Petroleum Engineer Jobs in Tennessee

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

Your Mission, Should You Choose to Accept As a Machine Learning Engineer, you will research, evaluate, and select appropriate machine Learning approaches and architectures based on the problem ...

Senior Machine Learning Engineer

Nashville, TN · On-site

$100K - $138K/yr

Your Mission, Should You Choose to Accept As a Machine Learning Engineer, you will research, evaluate, and select appropriate machine Learning approaches and architectures based on the problem ...

We are looking for a Senior Machine Learning Engineer to that will focus on researching, designing, training, and evaluating machine learning models to solve complex, real-world problems. We ...

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves asInovalon'scentral AI and machine learning hub. This team partners with Provider, Payer, and ...

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

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Machine Learning Petroleum Engineer information

Is ML a high paying job?

Machine Learning Petroleum Engineers typically earn high salaries due to their specialized skills in data analysis, modeling, and the oil and gas industry. Compensation varies based on experience, location, and certifications, but overall, it is considered a well-paying role within engineering fields.

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 engineers make $500,000?

Senior petroleum engineers, especially those with extensive experience, advanced technical skills, and leadership roles, can earn salaries of $500,000 or more annually. High compensation is often associated with working in major oil and gas companies, offshore environments, or in executive positions that require specialized expertise and certifications.

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 machine learning petroleum engineers with extensive experience, advanced skills in data analysis and modeling, and often working in leadership roles or specialized environments can earn $300,000 or more annually. High compensation typically involves working for major energy companies, possessing relevant certifications, and contributing to complex projects that impact production and exploration strategies.

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.

Will AI take over petroleum engineering?

AI can assist petroleum engineers by improving data analysis, reservoir modeling, and automation of routine tasks. However, the role of a petroleum engineer involves complex decision-making, field supervision, and problem-solving that require human expertise, making complete automation unlikely in the near future.
What cities in Tennessee are hiring for Machine Learning Petroleum Engineer jobs? Cities in Tennessee with the most Machine Learning Petroleum Engineer job openings:
Machine Learning Engineer

Machine Learning Engineer

Upperline Health

Nashville, TN • On-site

Full-time

Posted 29 days ago


Upperline Health rating

3.0

Company rating: 3.0 out of 10

Based on 10 frontline employees who took The Breakroom Quiz


Job description

Position Overview: We are looking for a talented Machine Learning Engineer to help build and maintain machine learning pipelines that support predictive healthcare models. This role is ideal for someone with strong data engineering skills and a passion for applying machine learning to real-world healthcare challenges.
Key Responsibilities:
  • Design and implement data pipelines using SQL and Python from various data sources.
  • Synthesize large medical claims data records into useable data features.
  • Collaborate with Data Scientists to build, refine, and deploy various machine learning models in Python.
  • Learn and apply SAS as needed for dataset generation (prior experience is not required).
  • Ensure data quality, reproducibility, and performance in the pipelines.
  • Contribute to best practices for data governance and model deployment.

Qualifications:
  • 2-5+ YOE as a Machine Learning Engineer or Data Scientist with a focus on engineering data builds.
  • Proficiency in SQL/Snowflake and Python; willingness to learn SAS as needed.
  • Experience building and combining data pipelines and working with large datasets.
  • Basic understanding of healthcare claims data (e.g., Medicare claims) preferred.
  • Familiarity with machine learning workflows (e.g., scikit-learn, pandas, NumPy).
  • Strong problem-solving and communication skills, sharp critical thinking skills.
  • Comfortable with a fast-paced workstream that requires flexibility to work on multiple projects or analyses at the same time.

Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

What Upperline Health employees say

Hours and flexibility

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