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.The OpportunityImubit 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.
Minimum Qualifications: - 4+years of engineering experience in refining, petrochemicals, chemicals, NGL or another continuous-process industry.
- BSc in Chemical Engineering, a related technical discipline or equivalent practical experience. Advanced degrees are a plus.
- A process engineering or process control background, with working knowledge of APC and optimization concepts such as gains, constraints and objective functions.
- Hands-on analysis of plant time-series data, including visualizing large data sets and drawing sound conclusions from them.
- Client-facing or operations-support experience, enough to earn credibility with plant engineers and operators.
- Willingness to travel up to 25%
- Strong communication and presentation skills
Preferred Qualifications: - Operating plant experience as a unit process engineer, control engineer or in operations support.
- Planning and economics (P&E) experience, including building, maintaining or running refinery LP models.
- Experience with APC or real-time optimization.
- A record of leading projects or implementations, including the technical relationship with the client.
- Scripting or data science experience, for example in Python.
- Exposure to plant data systems such as DCS, process historians or OPC.
- Background in consulting or a customer-facing vendor role serving industrial clients.
- Familiarity with AI, machine learning or advanced analytics applied to industrial processes.
- A record of improving plant performance with little or no capital spend.
Great to Have:- Modeling Judgment: Able to tell a learned relationship that reflects the process from one that does not and explain why.
- Industrial Fluency: Deep enough understanding of refinery and petrochemical units, control systems and economics to work with operators and engineers as a peer.
- Analytical Problem Solving: Enjoys working a messy process problem from data to answer and knows when to lean on teammates for help.
- Teaching and Enablement: Comfortable explaining technical concepts to operators, engineers and managers, building understanding that outlasts your time on site.
- Consultative Mindset: Treats the customer's outcome as your own, handles skeptics with patience and turns them into advocates.
- Ownership and Learning Agility: Drives your own work, finds answers independently and learns new technology fast.
What we offer:- Work at the cutting edge of industrial AI with Fortune 500 companies transforming how they operate.
- A two-track career path where management and individual contribution are equally serious destinations, with movement in both directions.
- Join a high-trust, cross-disciplinary team of engineers, data scientists, economists and product innovators.
- Flexible, remote-first working culture with a collaborative, ideas-welcome environment.
