SLB is seeking a proactive and technically strong individual to join our Dynamics team in
Calgary, Alberta as a
Process Engineering Simulation Software Developer. In this role, you will apply process engineering, numerical methods, software development, and emerging AI technologies to develop and improve high-fidelity simulation technology used to model complex process systems across oil & gas, LNG, refining, carbon capture, hydrogen, and emerging energy applications. We are looking for someone who enjoys tackling complex process engineering, numerical, and software development problems and developing the technology behind simulation software.
The ideal candidate has hands-on experience with numerical algorithms, numerical solvers, simulation engines, or scientific software, rather than experience primarily focused on using commercial simulation products. This role offers the opportunity to work across the full development lifecycle, from algorithm design and implementation to testing, validation, and deployment, while developing robust and high-performance solutions for time-dependent process systems. You will also have opportunities to explore AI, machine learning, and data-driven techniques to enhance simulation workflows and engineering productivity. The primary focus of the role remains process engineering, numerical simulation, and software development.
Roles and Responsibilities- Develop and improve simulation algorithms, process models, and numerical methods used for time-dependent (dynamic/transient) process systems.
- Design, implement, test, validate, and document simulation capabilities across the full product development lifecycle.
- Build clean, maintainable, and high-performance code primarily in C++ and Python, including supporting tools and workflows.
- Apply numerical methods with attention to stability, accuracy, and computational performance for complex engineering simulations.
- Collaborate with domain experts, software developers, testers, and customers to deliver reliable simulation solutions.
- Identify and address performance, stability, or accuracy issues in simulation models, solvers, and workflows.
- Explore and apply AI, machine learning, or data-driven techniques (where valuable) to enhance simulation workflows and productivity.
Qualifications and Experience- Bachelor's, Master's, or PhD in Chemical or Process Engineering is strongly preferred. Degrees in Applied Mathematics, Computer Science, or a closely related field will also be considered.
- Hands-on experience developing numerical algorithms, numerical solvers, process models, simulation engines, or scientific computing applications. Experience developing underlying simulation technology is preferred over experience focused primarily on using commercial simulation software.
- Strong programming skills in C++ and Python applied to numerical, computational, or engineering problems.
- Strong understanding of process engineering principles, process modeling, and process simulation.
- Understanding of numerical methods, mathematical modeling, numerical stability, and accuracy.
- Experience with dynamic/transient simulation, pressure-flow networks, thermodynamic modeling, unit operations, or related process simulation technologies is an asset.
- Interest or experience in AI/ML or data-driven modeling/optimization is an asset; experience applying AI/ML to engineering, simulation, or scientific computing problems is particularly valuable.
- Strong problem-solving skills and attention to engineering accuracy, numerical stability, and computational performance. Ability to work independently and collaborate effectively within a multi-disciplinary team. Growth mindset and enthusiasm for learning new technologies.
- Must be legally authorized to work and reside in Canada without company sponsorship.
