“Come work with us to explore the application of reinforcement learning to address a critical emissions problem in the oil & gas industry. If you are an RL/ML researcher or engineer looking to apply your skills to an important real-world industrial application, we want to talk to you. You will have the opportunity to innovate on a problem that has the real potential to reduce the emissions footprint of an entire legacy industry and get mentored by some of the best minds in AI during the process.”

- David Staszak, Lead Machine Learning Scientist and Mara Cairo, Product Owner, Advanced Technology

Description

About the Role

This is a paid Residency that will be undertaken over a twelve month period. The Resident will report to an Amii Scientist and regularly consult and work with our partners to share insights and engage in knowledge transfer activities. Successful candidates will be members of a cross-functional project team with backgrounds in ML research, project management, software engineering, and new product development. This is a rare opportunity to be mentored by world-class scientists and to develop something truly impactful.

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 Client

Our partner is a pioneering software provider of AI-driven industrial process optimization solutions, dedicated to transforming operational efficiency in the energy sector. Specializing in artificial lift and production optimization, this company leverages a sophisticated cloud-hosted software platform that employs advanced artificial intelligence and physics-based algorithms. These technologies are designed to optimize natural gas well operations, significantly reducing environmental impacts and enhancing overall well performance.

With a strong commitment to innovation and sustainability, the company is a leader in integrating cutting-edge AI models into its operations. This approach not only stabilizes production but also dramatically reduces methane emissions, setting new standards for environmental responsibility in the industry. Deployed across a vast network of wells, the company is at the forefront of driving substantial economic and ecological benefits, leading the way toward a more sustainable energy future.

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.

Industrial Process Control using Reinforcement Learning: By fine-tuning operational controls through data-driven RL models, you will help stabilize production while reducing operational costs and enhancing safety. This advanced application of RL in Plunger Lift operations is set to redefine industry standards for efficiency and environmental preservation.

What You Will Gain:

A unique opportunity to lead groundbreaking work in applying RL to critical environmental and operational challenges in the energy sector.

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:

• Publication record in peer-reviewed academic conferences or relevant journals in machine learning (specifically reinforcement learning or applied ML in industrial applications)

Non-Technical Requirements:

• Desire to take ownership of a problem and demonstrated leadership skills
• Interdisciplinary team player enthusiastic about working together to achieve excellence
• Capable of critical and independent thought
• Able to communicate technical concepts clearly and advise on the application of machine intelligence
• Intellectual curiosity and the desire to learn new things, techniques, and technologies

Why You Should Apply

Besides gaining industry experience, additional perks include:

• Work under the mentorship of an Amii Scientist for the duration of the project
• Participate in professional development activities
• Gain access to the Amii community and events
• Get paid for your work (a fair and equitable rate of pay will be negotiated at the time of offer)
• Build your professional network
• The opportunity for an ongoing machine learning role at the client's organization at the end of the term (at the client's discretion)

About Amii

One of Canada's three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world's top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

How to Apply

If this sounds like the opportunity you've been waiting for, please don't wait for the closing May 14, 2024 to apply - we're excited to add a new member to the Amii team for this role, and the posting may come down sooner than the closing date if we find the right candidate before the posting closes! This position will start in June 2024. When sending your application, please send your resume and cover letter indicating why you think you'd be a fit for Amii. In your cover letter, please include one professional accomplishment you are most proud of and why.

Applicants must be legally eligible to work in Canada at the time of application.

Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity, religion, gender identity, sexual orientation, age or disability. Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and won't be used in the selection process.