AI Integration Engineer for Bioreactor Systems - Remote

Overview

Cellcraft is a B2B biotechnology startup building intelligent infrastructure for biomanufacturing. Our flagship platform, Cellcraft IQ, applies machine learning and real-time control to bioreactors, enabling adaptive optimisation, predictive monitoring and autonomous process tuning. We are transforming bioprocessing into a data-driven engineering discipline that supports reliable, scalable production across biopharma and cultivated meat.

In Short

• Lead integration of Cellcraft IQ at customer sites, connecting to bioreactor systems via Modbus TCP, OPC UA, and PROFINET
• Design data pipelines for acquisition, cleaning and structuring of high-frequency sensor and process data
• Integrate ML models with embedded controllers and supervisory control systems
• Contribute to software architecture for scalable deployment of control and analytics systems
• Work directly with customer technical teams to scope, configure, and validate deployments
• Troubleshoot integration issues across diverse bioreactor OEM environments
• Document configurations, integration steps, and site-specific setups for each customer
• Act as the primary technical point of contact for customers during and after onboarding
• Feed field observations and customer feedback back to the product and engineering team
• May also include travel to customer facilities as required for on-site commissioning and support

Requirements

• Strong Python programming: NumPy, Pandas, SciPy, scikit-learn (production code, not just notebooks)
• Control systems fundamentals: State-space representation, PID tuning, stability analysis
• Time-series methods: Kalman filtering, ARIMA, or recurrent neural networks (LSTM/GRU)
• Real-time systems experience: Low-latency data processing, asynchronous programming, embedded constraints
• Industrial protocols: Modbus, OPC-UA, MQTT, or similar SCADA/IoT communication standards
• Understanding of feedback control in dynamic systems.
• Experience working with noisy sensor data and signal filtering techniques.
• Ability to interpret process dynamics from time-series data (lag, dead time, oscillations)
• Degree in Control Engineering, Computer Science, Chemical/Bioprocess Engineering, or related quantitative field
• Must have existing right to work in Singapore
• Fluent in English

Benefits

• Equity participation with the potential to share in the company’s long term success
• Opportunity to work on real world physical AI systems applied to biomanufacturing
• Build algorithms that move from experimental data to production scale systems
• Exposure to a fast growing field at the intersection of machine learning, biology and industrial automation
• Opportunity for significant responsibility and rapid career progression as the technology scales
• Contribute to technologies enabling sustainable food and medicine production
• Backed by the University of Cambridge Judge Business School and leading international venture capital investors
• Potential for a full time role and competitive salary following successful completion of the project