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Drilling Optimization Engineer Jobs (NOW HIRING)

Bedrock

Mud Engineer

Houston, TX · On-site

Mud Engineer Job Duties: * Prepare the drilling fluids for drilling operations ... Oversees the drilling fluid mud cleaning system's operation. * Assists in the optimization of the ...

Bedrock

Mud Engineer

Houston, TX · On-site

Mud Engineer Job Duties: * Prepare the drilling fluids for drilling operations ... Oversees the drilling fluid mud cleaning system's operation. * Assists in the optimization of the ...

Hawk Group

Completions Engineer

Houston, TX · On-site

$76K - $103K/yr

This role works closely with drilling, production, reservoir, geoscience, operations, finance, and ... Planning & Optimization * Collaborate with multidisciplinary teams to support field development ...

American Engineering Testing Inc

Drill Assistant

Fargo, ND · On-site

$23 - $26/hr

About Us At American Engineering Testing (AET), we believe that people are the heart of innovation ... Perform routine maintenance tasks on drilling equipment to ensure optimal functionality. * Review ...

Mariana Minerals

Drill and Blast Engineer

Moab, UT · On-site

In this role, you will lead blast design, oversee drilling programs, and partner closely with mine ... What You'll Do Blast Design & Optimization * Develop and refine blast patterns and charge designs ...

Hawk Group

Facility Engineer

Anchorage, AK · On-site

This role focuses on surface engineering and planning support for development drilling, frac ... optimization. This position is located primarily in Anchorage, Alaska and may include travel to the ...

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Drilling Optimization Engineer information

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$40

$59

$81

How much do drilling optimization engineer jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for drilling optimization engineer in the United States is $59.65, according to ZipRecruiter salary data. Most workers in this role earn between $43.27 and $73.56 per hour, depending on experience, location, and employer.

What is the difference between Drilling Optimization Engineer vs Drilling Engineer?

AspectDrilling Optimization EngineerDrilling Engineer
CredentialsBachelor's degree in Petroleum Engineering or related field; certifications in drilling practicesBachelor's degree in Petroleum Engineering or related field; similar certifications
Work EnvironmentFocus on optimizing drilling processes, data analysis, and efficiency improvementsOversees entire drilling operations, including planning, execution, and safety
Industry UsagePrimarily in companies seeking to improve drilling performance and reduce costsInvolved in all aspects of drilling projects, from design to execution

While both roles require similar educational backgrounds and certifications, the Drilling Optimization Engineer specializes in enhancing drilling efficiency through data analysis and process improvements. The Drilling Engineer oversees the entire drilling operation, ensuring safety and project success. The optimization engineer's role is more focused on technical analysis and performance enhancement within the broader drilling process.

How does a Drilling Optimization Engineer typically collaborate with drilling teams and other departments on a project?

A Drilling Optimization Engineer works closely with drilling teams, geologists, and data analysts to ensure efficient and safe drilling operations. They analyze real-time drilling data, recommend adjustments to parameters, and participate in daily meetings to discuss progress and address challenges. Effective communication is essential, as they often serve as a bridge between field operations and engineering teams, ensuring that best practices and innovative solutions are implemented across the project.

What are the key skills and qualifications needed to thrive as a Drilling Optimization Engineer, and why are they important?

To thrive as a Drilling Optimization Engineer, you need a solid background in petroleum engineering, drilling operations, and data analysis, often supported by a relevant engineering degree. Familiarity with drilling simulation software, real-time data monitoring systems, and industry certifications such as IWCF or Well Control are typically required. Strong problem-solving abilities, effective communication, and teamwork skills are crucial for collaborating with multidisciplinary teams and making informed decisions quickly. These competencies are vital for ensuring drilling efficiency, minimizing operational risks, and achieving cost-effective project outcomes.

What are Drilling Optimization Engineers?

Drilling Optimization Engineers are professionals in the oil and gas industry responsible for improving the efficiency, safety, and cost-effectiveness of drilling operations. They analyze data from drilling sites, recommend adjustments to drilling parameters, and collaborate with multidisciplinary teams to optimize drilling performance. Their work includes selecting appropriate drilling technologies, troubleshooting issues, and ensuring best practices are followed throughout the drilling process. The ultimate goal is to minimize non-productive time and maximize well productivity while maintaining safety and environmental standards.
More about Drilling Optimization Engineer jobs
What cities are hiring for Drilling Optimization Engineer jobs? Cities with the most Drilling Optimization Engineer job openings:
What states have the most Drilling Optimization Engineer jobs? States with the most job openings for Drilling Optimization Engineer jobs include:
What job categories do people searching Drilling Optimization Engineer jobs look for? The top searched job categories for Drilling Optimization Engineer jobs are:
Drilling Optimization Engineer jobs near you
Infographic showing various Drilling Optimization Engineer job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $124,067 per year, or $59.6 per hour.
Data Scientist, Reinforcement Learning

Data Scientist, Reinforcement Learning

ExxonMobil

Spring, TX • On-site

Part-time

Medical, Dental, Vision, Life, Retirement

Posted 7 days ago

ExxonMobil rating

6.1

Company rating: 6.1 out of 10

Based on 220 frontline employees who took The Breakroom Quiz

57th of 74 rated oil and gas companies

Job description

Your role on our team
Pioneer the application of reinforcement learning (RL) and sequential decision-making to high-impact challenges across ExxonMobil's upstream, downstream, and commercial operations.
Collaborate with engineers, scientists, and business stakeholders to turn complex operational and planning problems into deployable, production-grade RL solutions.
Advance the organization's capabilities in reinforcement learning, decision optimization, and autonomous control as part of the Modeling, Optimization, and Data Science (MODS) team.
What you will do
  • Design, develop, and deploy reinforcement learning solutions for real-world energy applications such as production optimization, process control, supply chain scheduling, drilling optimization, and resource allocation.
  • Formulate sequential decision problems by defining state spaces, action spaces, reward structures, transition dynamics, and operational constraints with domain experts.
  • Develop RL agents using model-free methods (e.g., PPO, SAC, TD3, DQN where appropriate) and model-based approaches, selecting methods based on problem requirements, safety, and data availability.
  • Build and use simulation environments and digital twins for offline training, policy evaluation, and validation before real-world deployment.
  • Apply safe and constrained RL techniques to ensure agents operate within operational and safety limits.
  • Integrate RL solutions with existing optimization, simulation, and control systems across real-time and planning use cases.
  • Partner with data scientists and ML engineers to operationalize solutions, including training pipelines, monitoring, retraining, and performance tracking.
  • Benchmark RL against traditional methods such as LP, MIP, heuristic search, MPC, and stochastic optimization to identify best-fit approaches.
  • Stay current with advances in offline RL, safe RL, multi-agent RL, hierarchical RL, and model-based RL.
  • Share knowledge, publish findings where appropriate, and mentor peers on RL best practices.

About you
Desired Skills:
  • Experienced AI/ML professional with strong expertise in reinforcement learning, sequential decision-making, optimization, and real-world deployment.
  • 5+ years of experience in AI/ML, optimization, or related fields, including at least 2 years in reinforcement learning, sequential decision-making, or optimal control.
  • Master's or PhD in Computer Science, Machine Learning, Operations Research, Control Theory, Robotics, Applied Mathematics, Engineering, or a related quantitative field.
  • Deep understanding of RL fundamentals, including MDPs, dynamic programming, temporal-difference learning, policy gradients, and actor-critic methods.
  • Proven experience building RL systems end-to-end, from environment and reward design through training, evaluation, and deployment.
  • Experience with simulation environments, digital twins, or system models.
  • Strong background in statistics, probability, optimization, control theory, and algorithm design.
  • Proficiency in Python, PyTorch and/or TensorFlow, plus RL tools such as Stable Baselines3, RLlib, and Gymnasium.
  • Strong communication and collaboration skills, including the ability to explain technical concepts to non-technical stakeholders.

Preferred Skills:
  • Experience applying RL or decision optimization in industrial domains such as process control, robotics, autonomous systems, supply chain, energy systems, or operations research.
  • Familiarity with offline (batch) RL, safe RL, and multi-agent RL.
  • Knowledge of model-based RL, MPC, and hybrid RL-control approaches.
  • Understanding of classical optimization methods and how RL complements them.
  • Experience with physics-informed or hybrid mechanistic/ML modeling and domain-informed reward or constraint design.
  • Familiarity with platforms such as Azure ML, Azure OpenAI, Databricks, and MLOps tools such as MLflow or Weights & Biases.
  • Experience in the energy industry or other asset-intensive, safety-critical sectors.

Your benefits
An ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance, and life.
We offer you:
  • Pension Plan: Enrollment is automatic and at no cost to you. The basic benefit is a monthly annuity to be paid to you in retirement for the rest of your life.
  • Savings Plan: You can contribute between 6% and 20% of your pay and are encouraged to enroll right away. If you contribute at least 6% to your savings plan, the Company will contribute a 7% match.
  • Workplace Flexibility: We have several programs such as "Flex your Day", providing ad-hoc flexibility around when and where you work, as well as longer-term programs such as leaves of absence and part-time work.
  • Comprehensive medical, dental, and vision plans.
  • Culture of Health: Programs and resources to support your wellbeing.
  • Employee Health Advisory Program: Provides confidential professional counseling for you and your family, including tools and resources promoting mental health and resiliency at no additional cost to you.
  • Disability Plan: Income replacement for when you cannot work due to illness or injury occurring on or off the job. Enrollment is automatic and at no cost to you.

More information on our Company's benefits can be found at www.exxonmobilfamily.com.
Please note benefits may be changed from time to time without notice, subject to applicable law.
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