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Leading the commercialization of ground-breaking technology that captures CO₂ directly from air is challenging and exhilarating. As a member of the CE team, you'll be surrounded by smart, adventurous, curious people committed to progressing our Direct Air Capture (DAC) and AIR TO FUELS TM technologies. We're a diverse team of innovators hailing from around the world with a shared vision, purpose, and commitment to deliver large scale climate change solutions. Our headquarters is in Squamish, B.and our presence is expanding in many other markets around the world as we commercialize our technologies. Many of our employees are drawn to CE because of the direct connection between the game-changing work we do and their own personal values. At our core, Carbon Engineering values integrity, growth, excellence in execution, and fun. Diversity is embraced, and we value an inclusive work environment where every employee has an equal opportunity to be heard. Reporting to the Director of Process Systems Engineering, the Senior Process Systems Engineer plays an essential role in analyzing and modeling CE technology process data using a wide range of tools and methodologies from simple mathematical and statistical functions, all the way to the most sophisticated and novel AI/ML approaches. The primary objective for this position is to lead and/or assist with various process modeling and data analytics projects that lead to improvements in core CE technologies and Oxy DAC operating plants. This role involves not only technical expertise but also effective communication and collaboration with various technical and business teams. C. working onsite at least 2 days a week. Responsibilities Data Collection and Preprocessing : Identify valuable data sources and automate collection processes. Undertake preprocessing of structured and unstructured data. Exploratory Data Analysis (EDA) of Process Data : Analyze and interpret large amounts of process/operation/experiment data and information to discover trends and patterns. Visualize data using appropriate techniques. Build predictive models, 1st principles models using commercial process modeling software and/or machine-learning algorithms. Apply statistical and machine learning techniques to analyze time-series data and extract meaningful insights. Develop custom data models, visualizations, and algorithms to interpret data. Optimize the performance of mathematical and ML models in production environments in enterprise structures. Enhance the MLOps culture and practices, enabling the team to create solutions with improved computational performance, scalability, and reliability. Collaborate with subject matter experts and engineers to understand their needs and help them with the end-to-end model development lifecycle. Post-graduate degree (PhD preferred) in Chemical Engineering or Process Systems Engineering (preferred), with a focus on mathematical & computational modeling, simulation, process design & control, optimization, data analytics, and/or ML. A proven track record of 7+ years of experience in Process Systems Engineering, Data Analytics, System Identification, Machine Learning, and data-driven/first-principles modeling and simulation. Proficiency in using commercial process simulation software (Aspen Plus, Aspen HYSYS, AVEVA, OLI Systems) Proficiency in data curation techniques such as Integration, Cleansing, and Feature Engineering. Expertise in data-driven ML algorithms, including regression, classification, time-series predictive models, dimension reduction, and data mining. Proficient in using Python and ML frameworks and libraries, such as TensorFlow, scikit-learn, or PyTorch. Experience with data visualization tools, such as Power BI, Matplotlib, Seaborn, Bokeh and ParaView. Experience with git version control. Experience in end-to-end model deployment (MLOps), covering data collection, productization, integration, and ongoing maintenance or retraining. Experienced with the implementation of Active Machine Learning (AML) Experience with formulating SQL queries. Experience with big data technologies and platforms, such as Hadoop, Spark, and NoSQL. Knowledge of Natural Language Processing, Reinforcement Learning, and Computer Vision. Experience in software development Knowledge of distributed ML development Carbon Engineering offers a competitive compensation package including extended health benefits. Our location in the outdoor recreation hub of Squamish gives you access to world class skiing, mountain biking, climbing, hiking, and other outdoor activities within minutes of the office, while in close proximity to Vancouver, one of the most beautiful and culturally diverse cities in Canada. Joining Carbon Engineering provides you more than a career – it's a calling for those who are ready to make a difference in climate action. Carbon Engineering is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants are encouraged to apply and will receive equal consideration for employment regardless of race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, disability, or age.