H2Ok Innovations is seeking an ML Applications Engineer to optimize process industrials and manufacturing for operational efficiency and sustainability using AI Co-pilot models and sensors, focusing initially on Clean-In-Place (CIP) processes.
Requirements
- Skilled in Python (NumPy, Pandas), MATLAB, or R; experience with ML libraries (Scikit-Learn, TensorFlow, PyTorch, JAX) is a plus
- Experienced in working with sensor and time-series data
- Strong Data Analysis Skills
Responsibilities
- Own the post-sales deployment of H2Ok’s optimization models for CIP and other processes
- Partner with customer teams to understand their operations, align on success metrics, and ensure models deliver in their environment
- Tune and improve ML models to unlock measurable water, energy, and time savings
- Turn process and sensor data into clear, compelling stories that drive action
- Lead customer presentations and workshops, communicating results to both technical and non-technical audiences, and guiding them to understand the data and our tool
- Collaborate with data science, software, and product teams to continually improve performance and reliability
Other
- Travel on-site to customer facilities (10–20%) to gain firsthand process understanding and ensure successful deployments
- Strong preference for a background in chemical engineering or chemistry. We will also consider process or mechanical engineering background.
- Confident communicator and presenter, comfortable leading discussions with customer stakeholders and creating compelling data visualizations
- Able to work in industrial plant environments, lab settings, and collaborative cross-functional teams
- Startup mindset — adaptable, hands-on, and focused on delivering impact
