Refining and Petrochemical Process Optimization Engineer

TL;DR: Imubit is looking for a top-notch Refining and Petrochemical Process Optimization Engineer, or what we call an Implementation Engineer (IE), to build the AI models that optimize live refineries and petrochemical plants. You take each model from scoping through closed-loop commissioning and teach the customer’s team to run it. This role is open to remote candidates in the US. Travel is required to client sites. About us: Imubit is redefining how industrial companies adopt and scale enterprise AI, adding millions of dollars to plant bottom lines while operating safely within energy and sustainability constraints. Our AI platform supports real-time optimization across complex, nonlinear industrial systems, enabling both autonomous and guided decision-making in live production environments. Backed by Insight Partners, Imubit brings together deep domain expertise from companies such as Exxon and Shell with leading AI talent from Google and other top innovators. With teams across the United States, Europe, Asia, and a growing international presence, Imubit is transforming operational optimization across industries ranging from refining and petrochemicals to cement and mining. The Opportunity Imubit helps customers take their plants beyond what they thought possible, with AI that optimizes live units in closed loop. As an Implementation Engineer, you are the process engineer who makes that happen on the customer's unit. You decide when a model is ready to run and see the results in the plant's economics. In this position, you will: - Work with the customer to scope optimization opportunities: the objective, the real constraints and the value case. Present the scope to their team. - Lead the technical side of each project: plan the modeling work, keep it on schedule and own the technical relationship with the customer’s engineers. - Analyze plant time-series data to establish feasibility.

Quantify data quality and tell the customer what can be built. - Build and evaluate AI models of the process, from inferential (soft sensor) models to process response models and closed-loop optimizers. - Judge whether each learned relationship reflects the real process and explain where a model departs from first principles. - Defend your modeling decisions in design reviews with customer engineers who know their unit well. - Commission models on site, train operators and engineers to use them and monitor closed-loop performance through customer sign-off. - Keep deployed models performing after go-live, troubleshooting issues and retraining around turnarounds and process changes. - Learn the systems integration side of delivery: plant data connections, tag configuration and the link between our platform and the control system. - Build the automations, documentation and training that let customers build, evaluate and monitor their own models. - Channel field insight back to our Product and R&D teams to shape the platform. In this position, you will: - Work directly with Imubit's founders and significantly impact company growth. - Contribute to an innovative and collaborative work environment - Challenge traditional ways of thinking and take ownership of creative ideas to drive meaningful change - Work closely with client teams both remotely and on-site to leverage their data to explore the process and its economic drivers. - Apply your Chemical Engineering knowledge to Imubit’s machine learning technology to continuously optimize live manufacturing processes. - Define process optimization strategies in collaboration with internal and client economic teams - Develop a deep understanding of the product’s usage patterns and help shape its future roadmap - Demonstrate and explain Imubit's technology to clients and train them to leverage it. - Understand client feedback and facilitate two-way communication with Imubit's R&D team.