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Machine Learning Resident
7 months ago
David Staszak, Lead Machine Learning Scientist and Mara Cairo, Product Owner, Advanced Technology
**Description**
**About the Role**
As a Machine Learning Resident specializing in Reinforcement Learning (RL), you will spearhead an innovative project that revolutionizes operational efficiency and environmental sustainability in the energy sector through autonomous process control and automation. Your primary task will be to develop, test, and refine advanced RL models designed to autonomously manage set points in upstream natural gas systems, significantly reducing methane emissions and enhancing operational efficiencies and worker safety.
This role demands a blend of theoretical knowledge and practical skills in machine learning, data science, and software engineering. You will collaborate closely with a team of researchers and industry professionals to integrate these models into existing systems, ensuring they not only meet but exceed the current industry standards. Additionally, your work will involve analyzing vast datasets to refine models that can predict and adapt to complex operational scenarios in real-time.
The models you develop will directly influence the operational strategies of natural gas assets valued at several billion dollars, marking a significant step forward in the use of AI for environmental and economic sustainability in the energy sector. Your efforts will play a crucial role in reducing global methane emissions related to methane venting and increase operational safety of field personnel in the energy sector.
**About the Project**
This focused role centers on developing and implementing an RL-based model for Autonomous Setpoint Management (ASPM) in the context of industrial process control and automation. The goal is to enhance the efficiency and sustainability of natural gas well operations by automating the management of operational set points, reducing the need for manual interventions and minimizing environmental impacts.
**Environmental Impact & Innovation**:
**Methane Emissions Reduction**: Your contributions will be vital in reaching our goal of reducing methane emissions by up to 90%, equivalent to removing approximately 300,000 gas-powered vehicles from the road each year. This substantial decrease in emissions underlines our commitment to environmental responsibility and our leadership in sustainable industry practices.
**What You Will Gain**:
Experience with high-impact projects that merge technical innovation with significant environmental benefits.
Exposure to a high-stakes industry environment, where your work will directly influence multi-billion dollar assets and play a key role in advancing sustainability initiatives.
Join our team and contribute to a project that not only pushes the technological envelope but also delivers substantial environmental benefits by dramatically reducing global methane emissions and advancing the sustainability goals of the energy industry.
**Required Skills / Expertise**
Are you passionate about building great solutions? Do you want to help move the needle on a large-scale emissions reduction problem? You’ll be presented with opportunities to both personally and professionally develop as you build your career. We’re looking for a talented and enthusiastic individual with a solid background in machine learning, specifically reinforcement learning.
**Key Responsibilities**:
- Develop, train, and evaluate RL agents specifically tailored to control the set points used in plunger lift methods within natural gas wells
- Design and optimize RL models to mitigate emissions and optimize operations in plunger lift systems
- Conduct applied research on ML techniques, with a focus to understanding and addressing the limitations of existing models
- Prepare and curate the relevant industrial control data for ML training
- Manage the productionalization and deployment of models to devices used to control key plunger lift processes
- Collaborate with project team and stakeholders to develop minimum viable products (MVPs) and client focused solutions
- Engage in regular client meetings, contributing to presentations and reports on project progress
- Optimize ML pipelines to ensure efficiency, scalability, and real-time processing capabilities
**Required Qualifications**:
- Completion of a graduate level program or higher (M.S./Ph.D) in Computer Science, ML or Engineering
- Research or project experience in machine learning, specifically using reinforcement learning tools and techniques
- Proficient in Python programming language and related ML frameworks, libraries and toolkits (e.g. Scikit learn, PyTorch, Pandas, Tensorflow, JAX)
- Familiarity with linux, Git version control, and writing clean code
- A positive attitude towards learning and understanding a new applied domain
- Must be legally eligible to work in Canada
**Preferred Qualifications**:
**Non-Technical Requirements**:
- Desire to take ownership of a problem and demo
