Senior Machine Learning Research Engineer

Sorry, this job was removed at 08:07 p.m. (CST) on Wednesday, Aug 06, 2025
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Modi‘in
In-Office
Artificial Intelligence • Machine Learning • Energy
The Role

TL;DR

Imubit is looking for a top-notch Senior Machine Learning R&D Engineer to take deep reinforcement learning algorithms where they have never gone before!

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 Reinforcement Learning (RL) developed by world-class machine learning scientists. 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:

We are looking for a passionate and experienced Machine Learning Research Engineer with a deep curiosity for understanding systems and a relentless drive to innovate. This role is perfect for a self-starter who thrives on tackling complex problems, exploring new ideas, and pushing boundaries. We want someone who doesn’t just solve given tasks but proactively envisions and develops new applications, challenges the status quo, and enhances models and methodologies to deliver cutting-edge solutions.

As a Machine Learning Engineer in our algo R&D, you will:

  • Conduct cutting-edge research to develop new functionalities for our models, expanding Imubit’s core deep reinforcement learning technology.
  • Advance the development of AutoML solutions to streamline and enhance machine learning workflows.
  • Drive the productization of your research, transforming innovative concepts into impactful, production-ready solutions.
  • Design and implement solutions with a focus on scalability, efficient runtime performance, and seamless deployment in production environments.

Requirements:

  • MSc in machine learning or related area
  • Education in machine learning at the level of advanced academic courses
  • At least 5 years of hands-on machine learning experience
  • Practical experience with deep learning
  • Self-reliant, proactive, with strong motivation and an inquisitive mind

Advantage:

  • Experience with deep learning on time series data (Transformers / recurrent models)
  • Experience with training neural networks in cloud environments (GCP/AWS) and distributed systems
  • Experience/education in signal processing/ control theory/ reinforcement learning
  • Academic research experience
  • Experience in leading projects and mentoring 

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The Company
HQ: Houston, TX
137 Employees
Year Founded: 2016

What We Do

At Imubit, we’re driven by a mission to tackle and solve the toughest challenges at chemical plants and refineries.

Our solution - the Imubit Closed Loop Neural Network™ - is an AI process optimization technology that enables plant managers to discover, engineer and monetize process optimization opportunities considered impossible until now.

As the first-ever technology of its kind in the industry, our neural network solution interconnects planning and economics, process engineering, process control and operations, in using historical data to learn subtle nonlinear dynamics, and optimize economically critical plant parameters in real time. This end-to-end solution is currently running in the world’s largest refining and petrochemical plants, unlocking millions of dollars a year in annual margin for operators.

Imubit is led by globally-renowned, Google-endorsed machine learning scientists and world-class hydrocarbon processing experts with over 220 years of industry experience.

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