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Machine Learning Petroleum Engineer Jobs (NOW HIRING)

Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and ...

Machine Learning Engineer

Austin, TX · On-site

$140K - $180K/yr

🚀 Machine Learning Engineer 📍 Austin, TX (Hybrid/Remote Considered) 💰 $140,000 - $180,000 Base We're partnering with a fast-growing energy firm looking to hire a Machine Learning Engineer to ...

New

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 ...

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 : • ...

Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and ...

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 ...

... 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 ...

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 ...

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 ...

Position Summary We are seeking a Machine Learning Engineer to help design, implement, and scale AI-enabled solutions that improve software delivery workflows, automate operational processes, and ...

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 ...

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Machine Learning Petroleum Engineer information

See salary details

$31.5K

$128.8K

$193.5K

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

As of Jun 26, 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.

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.
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:
Infographic showing various Machine Learning Petroleum Engineer job openings in the United States as of June 2026, with employment types broken down into 96% Full Time, 2% Part Time, and 2% Nights. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.
Machine Learning Engineer

Machine Learning Engineer

Paylocity

Schaumburg, IL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 18 days ago


Paylocity rating

8.5

Company rating: 8.5 out of 10

Based on 34 frontline employees who took The Breakroom Quiz

46th of 430 rated business services


Job description

Description:


Paylocity is an award-winning provider of cloud-based HR and payroll software solutions, offering the most complete platform for the modern workforce. The company has become one of the fastest-growing HCM software providers worldwide by offering an intuitive, easy-to-use product suite that helps businesses automate and streamline HR and payroll processes, attract and retain talent, and build a strong workplace culture.


While traditional HR and payroll providers automate basic HR processes such as payroll and benefits administration, Paylocity goes further by developing tools that HR and businesses need to compete for talent and deliver against the expectations of the modern workforce.


We give our employees what they need to succeed, including great benefits and perks! We offer medical, dental, vision, life, disability, and a 401(k) match, as well as perks that support you, your family, and your finances. And if it’s career development you desire, we provide that, too! At Paylocity, people matter most and have always been at the heart of our business.


Take your career to the next level at one of G2's Top 100 Software Companies. Explore our Product & Technology positions to see where you fit!


This is a fully remote position, allowing you to work from home or location of record within the U.S. with no in-office requirements. You must be available five days per week during designated work hours. The work arrangement for this role is subject to change based on business needs and individual performance. This may include adjustments to on-site requirements or schedule expectations, as necessary.


Machine Learning Engineer


Position Overview

Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and tooling to help enable data driven decisions and insights at scale for millions of Paylocity users.


As a Machine Learning Engineer in Product & Technology, you will help Paylocity build and deploy Machine Learning solutions, to help our teams build better products faster, more reliably, and at the scale we see in production for our customers. We develop machine learning models and infrastructure to support internal team strategies and collaborate closely with our data science organization to drive efficiency and best practices. Your primary focus will be to leverage your expertise in software development, machine learning algorithms, and data infrastructure to architect, develop, and optimize machine learning solutions. You will play a key role in driving the development of scalable and efficient machine learning models, contributing to the enhancement of product features, and the overall improvement of our infrastructure.


Our team is:

• Building infrastructure that can power ML and AI features for millions of users

• Building and deploying platform-wide recommendations to help companies follow HR best practices and allow employees to get the most out of our platform (Paylocity AI page)

• Baking AI Ethics into all our processes as a first-class citizen (Blog Post)

• Working in a collaborative fully remote environment with a desire to share ideas and continuously improve

• Invested in staying current in machine learning engineering by applying the newest tools, technologies, and practices

• Excited to work on cutting-edge technology!


Primary Responsibilities

The below represents the primary duties of the position, others may be assigned as needed. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.


• Collaborate closely with internal teams such as Data Science, Data Engineering, Paylocity’s Cloud Center of Excellence (CCOE), DevOps, and Delivery Platforms to understand requirements and ensure alignment of machine learning engineering solutions with overall business objectives and priorities.

• Leverage cutting-edge big data technologies on AWS utilizing Databricks and Spark to develop scalable and efficient machine learning solutions for millions of users.

• Create automated data and modeling pipelines, collaborating with internal teams to ensure smooth integration and deployment of machine learning software features.

• Lead the optimization of CI/CD workflows, ensuring scalability and resilience while addressing complex challenges in automation in partnership with DevOps and Delivery Platforms.

• Proactively identify and resolve issues/bugs, ensuring AppSec vulnerabilities are identified and corrected, working closely with Application Security and CCOE teams.

• Drive the adoption of best practices in machine learning engineering across teams, contributing to the development of formal training programs and materials for MLE tool adoption.

• Actively participate in cross-functional meetings and discussions, providing feedback, commentary, requirements, and questions to ensure alignment and drive project success.


Education and Experience

The below represents the primary duties of the position, others may be assigned as needed. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Bachelor’s degree with at least 3 years of machine learning engineering success or similar experience at software companies; or, advanced degree (master’s or PhD) preferred in machine learning engineering, data engineering, computer science, engineering, statistics, mathematics, data science, or other quantitative field, with no additional experience required.

• Experience in building production-grade machine learning models and infrastructure in Python.

• Strong background in advanced Python and big data technologies

• Experience with cloud infrastructure (i.e., AWS, GCP, or Azure).

• Demonstrated experience with Infrastructure as Code (IAC) tools (i.e. CDK, Pulumi, etc.).

• Demonstrated ability to leverage machine learning engineering to drive business results.

• Skilled at translating business problems into machine learning engineering problems and communicating the results to non technical audiences.

• Able to work in a collaborative environment with a desire to share your ideas.

• Able to work independently and complete tasks with high quality, but unafraid to seek out suggestions from other team members.

• Strong understanding of data engineering and software engineering fundamentals.

• Self-motivated, adaptable, and highly detail oriented.


Preferred Skills

• Professional or academic experience in HR, social science or psychology

• Contributions to open-source software in Python

• Enthusiastic about how machine learning and infrastructure can lead to a superior customer experience.

• Be invested in staying current in machine learning and infrastructure by applying new technologies and practices


Physical requirements

• Ability to sit for extended periods: The role requires sitting at a desk or workstation for long periods, typically 7-8 hours a day.

• Use of computer and phone systems: The employee must be able to operate a computer, use phone systems, and type. This includes using multiple software programs and inquiries simultaneously.


Paylocity is an equal-opportunity employer. Paylocity is committed to the full inclusion of all individuals. We recruit, train, compensate, and promote regardless of race, religion, color, national origin, sex, disability, age, veteran status, and other protected status as required by applicable law. At Paylocity, we believe diversity makes us better.

We embrace and encourage our employees’ differences in age, culture, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion or spiritual belief, sexual orientation, socio-economic status, veteran status, and other characteristics that make our employees unique. We actively cultivate these differences through our employee resource groups (ERGs), employee experiences, perspectives, talents, and approaches to drive innovation in the software and services we provide our customers.

We comply with federal and state disability laws and make reasonable accommodations for applicants and employees with disabilities. To request reasonable accommodation in the job application or interview process, please contact LeaveBenefits@paylocity.com. This email address is exclusively designated for such requests, aligning with federal and state disability laws. Please do not send resumes to this email address, as they will be removed.


The base pay range for this position is $106,600 - $152,300/yr; however, base pay offered may vary depending on job-related knowledge, skills, and experience. This position offers a full range of benefits outlined here . This information is provided per the relevant state and local pay transparency laws for the location in which this position will be performed. Base pay information is based on market location. Applicants should apply via www.paylocity.com/careers.

Requirements:



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