TL;DR:

Imubit is looking for a top-notch chemical engineer to help transcend process industries with breakthrough machine learning technology.

About us:

Imubit directly controls and optimizes refineries and chemical plants with AI to add millions of dollars to the plant bottom line while managing safe operating limits, energy efficiency, and sustainability objectives. Imubit’s Closed Loop Neural Network platform allows customers to leverage an advanced form of AI called Reinforcement Learning (RL). Through our patented approach to apply RL for industrial processes, industry leaders have been able to fundamentally change the way they optimize their plants and improve profitability in real-time. Imubit’s solution is currently optimizing the manufacturing facilities of Fortune-500 companies. Imubit has combined the industry expertise from companies like Exxon and Shell with award-winning data scientists endorsed by Google. Imubit is backed by tier-1 venture capital firms such as Insight Partners.

We are looking for:

You, a Chemical Engineer, with an interest in modeling and optimization; previous experience in either process engineering, process troubleshooting, or process control is required. You want to be a part of what’s next in the industry using process optimization software and machine learning technology to solve core issues and redefine an industry. You aspire to be on a pioneering fast-growing team that works closely with clients to solve their difficult problems and provide them with proven economical results. You are self-motivated and love learning new technological and scientific disciplines. You recognize a once-in-a-career opportunity and seize it.

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.

Must-Have Qualifications:

• BSc in Chemical Engineering
• Background in chemical engineering or process engineering
• 4-8 years of industry engineering experience (refining, petrochemical, NGL/ethanol, etc.)
• Willingness to travel to client sites.
• For those in Houston, you must be onsite in the Houston office 2 -3 days per week (hybrid work environment)
• For those who reside in other states within the U.S., you may work remotely, however, you will be required to travel to client sites and come to Houston from time to time. (15%-25%)

Nice to have

• Optimization or Linear modeling experience is a plus
• Onsite manufacturing experience in an operations support role
• Client- facing experience 

Imubit provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Imubit complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Imubit does not accept or retain unsolicited CVs or phone calls and/or respond to them or to any third party representing job seekers.

No visa sponsorship is available for this position.