ZipRecruiter

Log In

1

Machine Learning Petroleum Engineer Jobs in Raleigh, NC

CoVar

Software Engineer

Durham, NC · On-site

They are seeking a motivated Software Engineer to develop and maintain applications that involve data processing and machine-learning algorithm integration. Responsibilities : • develop and ...

CoVar

Software Engineer

Durham, NC

Software Engineer About CoVar CoVar is a small, mission-driven AI/ML R&D software company based in ... We build advanced software and machine learning systems that help the Department of Defense detect ...

SINNOVATEK SERVICES LLC

Automations Engineer

Middlesex, NC · On-site

$95K - $125K/yr

... machine learning models. ● Work on projects using Python, C++, or similar to interface with ... engineering logs. ● Ensure safe and organized work areas in labs and on production floors. ● ...

DPR Construction

MLOps Engineer

Raleigh, NC

We are looking for aMLOps Engineerto join our team and contribute to developing robust data solutionsto support our Machine Learning,Data Science, Data Engineering and Software Engineering. Position ...

Deloitte

Senior AI Engineer - SFL Scientific

Raleigh, NC

$101K - $139K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

DPR Construction

MLOps Engineer

Raleigh, NC · On-site

We are looking for a MLOps Engineer to join our team and contribute to developing robust data solutions to support our Machine Learning, Data Science, Data Engineering and Software Engineering.

UnitedHealth Group

Lead AI/ML Engineer - Remote

Raleigh, NC · On-site +1

$99K - $131K/yr

The engineer applies deep learning technologies to enable computers to visualize, learn, and ... Develop and implement AI and machine learning strategies across several healthcare domains

UnitedHealth Group

Lead AI/ML Engineer - Remote

Raleigh, NC · On-site +1

$99K - $131K/yr

The engineer applies deep learning technologies to enable computers to visualize, learn, and ... Develop and implement AI and machine learning strategies across several healthcare domains

next page

Showing results 1-20

All JobsMachine Learning Petroleum Engineer JobsMachine Learning Petroleum Engineer Jobs in Raleigh, NC

Machine Learning Petroleum Engineer information

See Raleigh, NC salary details

$30.6K

$125.2K

$188.1K

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

As of Jul 5, 2026, the average yearly pay for machine learning petroleum engineer in Raleigh, NC is $125,174.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,700.00 and $150,700.00 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.
What are popular job titles related to Machine Learning Petroleum Engineer jobs in Raleigh, NC? For Machine Learning Petroleum Engineer jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Petroleum Engineer jobs in Raleigh, NC look for? The top searched job categories for Machine Learning Petroleum Engineer jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Machine Learning Petroleum Engineer jobs? Cities near Raleigh, NC 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 Raleigh, NC as of June 2026, with employment types broken down into 87% Full Time, 9% Part Time, 2% Contract, and 2% Nights. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $125,174 per year, or $60.2 per hour.
Senior Machine Learning Engineer III ***Raleigh, NC***

Senior Machine Learning Engineer III ***Raleigh, NC***

LexisNexis

Raleigh, NC • On-site

$118K - $219K/yr

Full-time

Posted 15 days ago

LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

111th of 437 rated business services

Job description

Are you looking to develop your Machine Learning Engineer career?
Do you enjoy coaching others to achieve high standards?
This is a full-time position based in Raleigh, NC.
(Hybrid - 3 days in office)
About the Role
We are seeking a Consultant-level Machine Learning Engineer to lead the implementation and scaling of AI systems for legal products. This role focuses on how to build and scale-owning system architecture, infrastructure, and productionization of ML/LLM solutions.
You will partner with Data Scientists to turn validated models and prototypes into reliable, high-performance, customer-facing systems.
Key Responsibilities
  • Architect and implement scalable ML/LLM systems in production.
  • Build and deploy LLM applications, including RAG pipelines and agentic systems.
  • Implement hybrid search systems (semantic + lexical) using embeddings and search platforms.
  • Develop and maintain APIs, microservices, and model serving infrastructure.
  • Build data pipelines and streaming systems for large-scale data processing.
  • Define and develop reusable frameworks, libraries, and infrastructure for AI/ML across teams.
  • Optimize systems for latency, scalability, reliability, and cost efficiency.
  • Establish best practices for deployment, monitoring, observability, and CI/CD.
  • Collaborate with Data Scientists to productionize models and integrate into products.
  • Provide technical leadership in system design and engineering standards.

Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • Strong experience implementing and scaling production ML/LLM systems.
  • Deep experience with LLM application development, including RAG and prompt orchestration.
  • Strong experience designing and implementing agentic systems using agent frameworks (e.g., LangChain, LangGraph, AutoGen, Google ADK), including orchestration of multi-step workflows in production environments.
  • Strong experience with hybrid search (semantic + lexical), embeddings, and search platforms (e.g., Solr, OpenSearch).
  • Expertise in distributed systems and cloud-native development, including AWS (S3, DynamoDB).
  • Experience with streaming and messaging systems (e.g., Kafka, SQS) and caching (e.g., Redis).
  • Proficiency in Python and experience with systems languages (e.g., Rust, Go, Scala).
  • Experience building scalable APIs (REST/GraphQL).
  • Experience with containerization and orchestration (Docker, Kubernetes).
  • Strong software engineering fundamentals (system design, testing, CI/CD).

Preferred Qualifications
  • Experience with LLM platforms (e.g., ChatGPT/OpenAI, Claude, Gemini, LangChain, Google ADK).
  • Experience with DevOps and infrastructure as code (e.g., Terraform, CloudFormation, Jenkins).
  • Experience with big data technologies (e.g., Spark, Hadoop).
  • Familiarity with graph databases (e.g., Dgraph, Neo4j, Neptune).
  • Experience building high-availability, low-latency systems.
  • Experience in legal or regulatory domains.

Key Competencies
  • Strong system architecture and scalability mindset.
  • Ownership of implementation, performance, and reliability.
  • Ability to translate data science solutions into production systems.
  • Cross-functional collaboration with DS, product, and platform teams.
  • Excellent debugging, optimization, and operational skills.
  • Clear communication of technical designs and trade-offs.

#AIFluent
U.S. National Base Pay Range: $118,300 - $219,800. Geographic differentials may apply in some locations to better reflect local market rates.This job is eligible for an annual incentive bonus.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here
Please read our Candidate Privacy Policy.
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
USA Job Seekers:
EEO Know Your Rights.

What LexisNexis employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply