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Machine Learning Petroleum Engineer Jobs in Indiana

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 ...

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 ...

Senior Machine Learning Engineer

Union City, IN · On-site +1

$95.20K - $130.70K/yr

About the Team- We are looking for a Senior ML Engineer to join the group of Machine Learning Engineers working on developing a cutting-edge GenAI platform, LLM-powered applications, and fundamental ...

Senior Machine Learning Engineer

Union City, IN · On-site +1

$95.20K - $130.70K/yr

About the Team- We are looking for a Senior ML Engineer to join the group of Machine Learning Engineers working on developing a cutting-edge GenAI platform, LLM-powered applications, and fundamental ...

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Machine Learning Petroleum Engineer information

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.

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 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 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 cities in Indiana are hiring for Machine Learning Petroleum Engineer jobs? Cities in Indiana with the most Machine Learning Petroleum Engineer job openings:
Infographic showing various Machine Learning Petroleum Engineer job openings in Indiana as of May 2026, with employment types broken down into 6% Internship, 91% Full Time, and 3% Temporary. Highlights an 94% In-person, and 6% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Indeed

Indianapolis, IN • On-site

Other

Medical, PTO

This job post has expired today. Applications are no longer accepted.


Indeed rating

9.5

Company rating: 9.5 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

6th of 185 rated software companies


Job description

Our Mission

Our Mission

As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and creating the best experience for job seekers.

(*Comscore, Total Visits, March 2025)

Day to Day

The Machine Learning Engineer I role partners closely with business partners across various functions to help execute strategic initiatives that increase revenue, drive operational scale, and improve efficiency for continuous growth. 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 packages and research publications, and creatively adapt models for solving business problems across Indeed.

Work spans classical ML through LLM systems. You improve search and retrieval quality using real user signals. Execution includes experiments, iteration, and production reliability at scale. You collaborate with engineers, data scientists, and product teams to define problems, test approaches, and ship measurable improvements.

Responsibilities

  • Build AI/ML systems for search, ranking, and recommendations

  • Develop LLM retrieval and generation workflows

  • Improve search and ranking relevance

  • Design metrics and run experiments

  • Monitor model quality, latency, and cost

  • Debug data, models, and system issues

  • Build training, inference, and eval pipelines

Skills/Competencies

  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 2 years of related experience; or an advanced degree without experience

  • Experience building ML models in Python; solid software engineering and algorithms fundamentals

  • Experience developing backend services in Java/Kotlin for ML-driven systems and features

  • Experience writing clean, testable, and maintainable production code

  • Experience working with structured and unstructured data, including SQL for large-scale data querying, and building scalable data pipelines and features from data

  • Experience integrating ML models into search systems using engines such as OpenSearch or similar, with familiarity in container orchestration for deployment with senior guidance

  • Excellent understanding of model evaluation techniques, feature engineering, experiment design, and familiarity with LLM systems (RAG, embeddings, output evaluation)

Salary Range Transparency

Tier 1 - United States of America 118,000 - 176,000 USD per year

Tier 2 - United States of America 130,000 - 196,000 USD per year

Tier 3 - United States of America 143,000 - 215,000 USD per year

Tier 4 - N/A

Tier 5 - United States of America 163,000 - 245,000 USD per year

Salary Range Disclaimer

The salary range for this role reflects the minimum and maximum compensation for the role. Offers are typically made between the range minimum and the range midpoint. Actual compensation will be determined based on job-related skills, experience, and expertise, as evaluated during the interview process. The range(s) listed is just one component of Indeed's total compensation package for employees. Other rewards may include quarterly bonuses, Restricted Stock Units (RSUs), a Paid Time Off policy, and many region-specific benefits. Compensation may also vary based on where a role is performed, as work locations are grouped into geographic pay tiers to reflect cost of labor differences in different geographic markets. Candidates can view geographic pay tiers by location on our career site (https://www.indeed.com/careers/paytiers), and recruiters can confirm how location is considered for a specific role.

Benefits - Health, Work/Life Harmony, & Wellbeing

Indeed is deeply committed to building a workplace and global community where inclusion is not only valued, but prioritized. We're proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, family status, marital status, sexual orientation, national origin, genetics, neuro-diversity, disability, age, or veteran status, or any other non-merit based or legally protected grounds.

Indeed provides reasonable accommodations to qualified individuals with disabilities in the employment application process. To request an accommodation, please visit https://www.indeed.com/careers/accommodations. If you are requesting accommodation for an interview, please reach out at least one week in advance of your interview.

For more information about our commitment to equal opportunity/affirmative action, please visit our Careers page (https://www.indeed.com/careers).

Equal Opportunities and Accommodations Statement

Inclusion and belonging are fundamental to our hiring practices and company culture, forming an integral part of our vision for a better world of work. At Indeed, we're committed to the wellbeing of our employees and on a mission to make this the best place to work and thrive. We believe that fostering an inclusive environment where every employee feels respected and accepted benefits everyone, fueling innovation and creativity.

We value diverse experiences, including those who have had prior contact with the criminal legal system. We are committed to providing individuals with criminal records, including formerly incarcerated individuals, a fair chance at employment.

Those with military experience are encouraged to apply. Equivalent expertise demonstrated through a combination of work experience, training, military experience, or education is welcome.

Indeed's Employee Recruiting Privacy Policy

Like other employers Indeed uses our own technologies to help us find and attract top talent from around the world. In addition to our site's user and privacy policy found at https://www.indeed.com/legal, we also want to make you aware of our recruitment specific privacy policy found at https://www.indeed.com/legal/indeed-jobs.

Agency Disclaimer

Indeed does not pay placement fees for unsolicited resumes or referrals from non-candidates, including search firms, staffing agencies, professional recruiters, fee-based referral services, and recruiting agencies (each individually, an "Agency"), subject to local laws. An Agency seeking a placement fee must obtain advance written approval from Indeed's internal Talent Acquisition team and execute a fee agreement with Indeed for each job opening before making a referral or submitting a resume for that opening.

AI Notice

Indeed is committed to ensuring fairness and transparency throughout our hiring process. We use artificial intelligence (AI) tools to assist in the screening, assessment, and selection of applicants for this position by analyzing information provided in resumes and applications. Our use of AI does not replace human decision-making.

Unless otherwise notified, Indeed does not use AI constituting an AEDT or an ADMT as those tools are defined in applicable laws.

The deadline to apply to this position is 6/1/2026. Job postings may be extended at the hiring team's discretion based on applicant volume.

Reference ID: 46644

Reference ID: 46644