Sr. Process Systems Engineer
Carbon Engineering
- Squamish, BC
- $93,330 per year
- Permanent
- Full-time
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.The successful candidate will be based in either Vancouver or Squamish, B.C. working onsite at least 2 days a week.ResponsibilitiesData Collection and Preprocessing:
- Identify valuable data sources and automate collection processes.
- Undertake preprocessing of structured and unstructured 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.
- Combine models through ensemble modeling.
- 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.
- Work closely with users to respond effectively to issues and resolve problems in a timely manner.
- Enhance the MLOps culture and practices, enabling the team to create solutions with improved computational performance, scalability, and reliability.
- Conduct research, experiments, and collaborate with industry leaders.
- Collaborate with subject matter experts and engineers to understand their needs and help them with the end-to-end model development lifecycle.
- Communicate with stakeholders and leadership to provide updates on progress and identify areas for improvement.
- Provide thought leadership by staying abreast of best practices.
Education and Knowledge:
- 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.
- Knowledge of Theory-informed ML e.g. PINNs and Neural Operator.
- Experienced with the implementation of Active Machine Learning (AML)
- Experience with formulating SQL queries.
- Familiarity with cloud-native architecture using containerized microservices (e.g., AWS, Azure, Google Cloud).
- Knowledge and experience with orchestration for scale-out, particularly Kubernetes.
- Experience with big data technologies and platforms, such as Hadoop, Spark, and NoSQL.
- Knowledge of JAX.
- Knowledge of Natural Language Processing, Reinforcement Learning, and Computer Vision.
- Experience in API development with FastAPI.
- Experience in software development