Job Details

Job Duties

We are seeking a pioneering Reinforcement Learning (RL) Scientist to join our Innovation team.

• You will be instrumental in the design, development, and deployment of intelligent systems that automate and optimize the drilling process.
• Leveraging your expertise in RL, you will build and train agents to make real-time, data-driven decisions that enhance safety, increase efficiency, and maximize the economic value of our customers’ drilling operations.
• This is a unique opportunity to apply state-of-the-art AI techniques to a high-impact oil and gas domain, transforming how we discover and produce energy.

Qualifications

• Master's or Ph.D. in Computer Science, Petroleum Engineering, Mechanical Engineering, or a related quantitative field.
• Strong theoretical and practical knowledge of core reinforcement learning concepts and algorithms (e.g., Deep Q-Networks, Proximal Policy Optimization, Actor-Critic methods).
• Programming: Proficiency in Python and experience with at least one major deep learning framework (PyTorch or TensorFlow).
• A solid understanding of machine learning fundamentals, statistics, and optimization.

Preferred Qualifications:

• Hands-on experience or a strong understanding of drilling operations or geomechanics. Familiarity with key drilling parameters and performance metrics.
• Proven experience applying RL to real-world control systems, robotics, or other physical systems with dynamic environments.
• Experience with drilling or reservoir simulation software (e.g., COMPASS, DrillSim, Nexus) or other physics-based simulators.
• A track record of publications in relevant conferences or industry journals (e.g., SPE Journal).

Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs.  Depending on education, experience, and skill level, a variety of job opportunities might be available including Senior Technical Professional Data Science  or Principal Technical Professional Data Science.

Job Duties

We are seeking a pioneering Reinforcement Learning (RL) Scientist to join our Innovation team.

• You will be instrumental in the design, development, and deployment of intelligent systems that automate and optimize the drilling process.
• Leveraging your expertise in RL, you will build and train agents to make real-time, data-driven decisions that enhance safety, increase efficiency, and maximize the economic value of our customers’ drilling operations.
• This is a unique opportunity to apply state-of-the-art AI techniques to a high-impact oil and gas domain, transforming how we discover and produce energy.

Qualifications

• Master's or Ph.D. in Computer Science, Petroleum Engineering, Mechanical Engineering, or a related quantitative field.
• Strong theoretical and practical knowledge of core reinforcement learning concepts and algorithms (e.g., Deep Q-Networks, Proximal Policy Optimization, Actor-Critic methods).
• Programming: Proficiency in Python and experience with at least one major deep learning framework (PyTorch or TensorFlow).
• A solid understanding of machine learning fundamentals, statistics, and optimization.

Preferred Qualifications:

• Hands-on experience or a strong understanding of drilling operations or geomechanics. Familiarity with key drilling parameters and performance metrics.
• Proven experience applying RL to real-world control systems, robotics, or other physical systems with dynamic environments.
• Experience with drilling or reservoir simulation software (e.g., COMPASS, DrillSim, Nexus) or other physics-based simulators.
• A track record of publications in relevant conferences or industry journals (e.g., SPE Journal).

Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs.  Depending on education, experience, and skill level, a variety of job opportunities might be available including Senior Technical Professional Data Science  or Principal Technical Professional Data Science.

Job Duties

We are seeking a pioneering Reinforcement Learning (RL) Scientist to join our Innovation team.

• You will be instrumental in the design, development, and deployment of intelligent systems that automate and optimize the drilling process.
• Leveraging your expertise in RL, you will build and train agents to make real-time, data-driven decisions that enhance safety, increase efficiency, and maximize the economic value of our customers’ drilling operations.
• This is a unique opportunity to apply state-of-the-art AI techniques to a high-impact oil and gas domain, transforming how we discover and produce energy.

Qualifications

• Master's or Ph.D. in Computer Science, Petroleum Engineering, Mechanical Engineering, or a related quantitative field.
• Strong theoretical and practical knowledge of core reinforcement learning concepts and algorithms (e.g., Deep Q-Networks, Proximal Policy Optimization, Actor-Critic methods).
• Programming: Proficiency in Python and experience with at least one major deep learning framework (PyTorch or TensorFlow).
• A solid understanding of machine learning fundamentals, statistics, and optimization.

Preferred Qualifications:

• Hands-on experience or a strong understanding of drilling operations or geomechanics. Familiarity with key drilling parameters and performance metrics.
• Proven experience applying RL to real-world control systems, robotics, or other physical systems with dynamic environments.
• Experience with drilling or reservoir simulation software (e.g., COMPASS, DrillSim, Nexus) or other physics-based simulators.
• A track record of publications in relevant conferences or industry journals (e.g., SPE Journal).

Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs.  Depending on education, experience, and skill level, a variety of job opportunities might be available including Senior Technical Professional Data Science  or Principal Technical Professional Data Science.

Job Duties

We are seeking a pioneering Reinforcement Learning (RL) Scientist to join our Innovation team.

• You will be instrumental in the design, development, and deployment of intelligent systems that automate and optimize the drilling process.
• Leveraging your expertise in RL, you will build and train agents to make real-time, data-driven decisions that enhance safety, increase efficiency, and maximize the economic value of our customers’ drilling operations.
• This is a unique opportunity to apply state-of-the-art AI techniques to a high-impact oil and gas domain, transforming how we discover and produce energy.

Qualifications

• Master's or Ph.D. in Computer Science, Petroleum Engineering, Mechanical Engineering, or a related quantitative field.
• Strong theoretical and practical knowledge of core reinforcement learning concepts and algorithms (e.g., Deep Q-Networks, Proximal Policy Optimization, Actor-Critic methods).
• Programming: Proficiency in Python and experience with at least one major deep learning framework (PyTorch or TensorFlow).
• A solid understanding of machine learning fundamentals, statistics, and optimization.

Preferred Qualifications:

• Hands-on experience or a strong understanding of drilling operations or geomechanics. Familiarity with key drilling parameters and performance metrics.
• Proven experience applying RL to real-world control systems, robotics, or other physical systems with dynamic environments.
• Experience with drilling or reservoir simulation software (e.g., COMPASS, DrillSim, Nexus) or other physics-based simulators.
• A track record of publications in relevant conferences or industry journals (e.g., SPE Journal).

Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs.  Depending on education, experience, and skill level, a variety of job opportunities might be available including Senior Technical Professional Data Science  or Principal Technical Professional Data Science.