Reservoir - Machine Learning Software Engineer (Houston, TX)

Sinopec Group; Houston (TX); On-site; USD 90,000 - 130,000; Full time

Job summary

A leading company in the oil and gas industry is seeking a Machine Learning Software Engineer to develop advanced ML-driven software for reservoir studies. The role involves creating innovative solutions for reservoir analysis, collaborating with multidisciplinary teams, and enhancing model performance. Candidates should have strong expertise in ML algorithms, Python, and relevant libraries, along with a Bachelor's degree in Computer Science or a related field.

Qualifications

• 3+ years of experience in ML software development.
• Expertise in machine learning algorithms, including deep learning.

Responsibilities

• Develop and implement ML algorithms for reservoir behavior.
• Collaborate with geoscientists and engineers to integrate ML solutions.

Skills

Machine Learning

Python

Problem Solving

Education

Bachelor's degree in Computer Science

Bachelor's degree in Software Engineering

Tools

TensorFlow

PyTorch

Scikit-learn

Job description

Reservoir - Machine Learning Software Engineer (Houston, TX)

Machine Learning Software Engineer – Reservoir Houston, TX

Job Title: Machine Learning Software Engineer

Sinopec Tech Houston LLC, a research branch of Sinopec, focuses on advancing technological innovations in the oil and gas industry. Our team is committed to applying cutting-edge ML (machine learning) techniques to enhance reservoir management, optimize exploration and production, and conduct in-depth studies of in-situ stress within oil and gas reservoirs.

We are seeking an experienced ML Software Engineer to join our multidisciplinary team, focusing on developing advanced ML-driven software products for reservoir studies. The role involves creating innovative solutions for analyzing and modeling reservoir characteristics and simulations, including well performance prediction, in-situ stress analysis, and other reservoir properties to support efficient oil and gas exploration and production.

Essential Functions:

1. Develop and implement ML algorithms to model reservoir behavior, focusing on in-situ stress analysis, geomechanical modeling, and fluid dynamics.
2. Build and maintain machine learning models and tools that support reservoir characterization, real-time monitoring, and optimization.
3. Collaborate with geoscientists, engineers, and data scientists to integrate ML solutions into existing workflows and decision-making processes.
4. Enhance model performance and optimize for use in in-situ stress and large-scale reservoir simulations.
5. Conduct research to stay at the forefront of ML technologies in the oil and gas industry, emphasizing practical applications.
6. Contribute to developing ML-based software solutions that streamline reservoir study processes and increase operational efficiency.
7. Prepare clear and detailed technical reports and present findings to management.
8. Participate in industry technical conferences, expand and maintain industry networks.
9. Assist related teams in formulating new technology R&D plans and implementation strategies.
10. Complete projects on time, with high quality, within budget.

Required Knowledge, Skills, and Abilities:

• 3+ years of experience in ML software development, preferably in geosciences, petroleum engineering, or related fields.
• Expertise in machine learning algorithms, including deep learning, reinforcement learning, and predictive modeling.
• Strong proficiency in Python and relevant ML libraries (TensorFlow, PyTorch, Scikit-learn, Commercial LLM-API).
• Experience with geological modeling, reservoir simulation, or in-situ stress analysis is a plus.
• Proven track record of deploying ML models in production environments.
• Knowledge of cloud platforms (AWS, GCP, Azure) and modern development tools.
• Strong problem-solving skills and ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.

Preferred Knowledge, Skills, and Abilities:

• Familiarity with latest ML trends and their applications in energy, especially subsurface studies.
• Bachelor’s degree or higher in Computer Science or related fields preferred.
• Experience in ML-driven reservoir management or oil and gas applications is advantageous.

Minimum Education, Credentials, Licenses, and Experience:

• Bachelor’s degree or higher in Computer Science, Software Engineering, geomechanics, geology, reservoir simulation, or related fields involving coding.
• At least 3 years of experience as a Software Developer in geosciences or related fields.
• Some travel may be required (<10%).
• Legally eligible to work in the U.S. without sponsorship.

Disclaimers: The above statements reflect the general duties and competencies necessary for this role and are not exhaustive. Responsibilities may evolve over time.

We are an Equal Employment Opportunity employer. We do not discriminate based on race, religion, gender, age, disability, or other protected characteristics. For assistance due to disability, contact [e-mail] or call 1-832-831-1200.

Apply directly at: www.sinopecthc.com