About the Role
The role involves designing and deploying AI-driven solutions to improve the monitoring, control, and scalability of bioreactor operations. The candidate will bridge machine learning models with biological process data to enhance system responsiveness and yield.
Responsibilities
- Develop machine learning models tailored to bioprocess data streams
- Integrate AI algorithms into existing bioreactor control software
- Collaborate with wet-lab teams to validate model predictions
- Optimize real-time data pipelines for low-latency inference
- Design feedback loops between sensors and AI controllers
- Troubleshoot integration issues between hardware and software layers
- Ensure model interpretability for regulatory compliance
- Maintain version control for AI models and deployment scripts
- Monitor system performance and implement iterative improvements
- Document model architecture and integration workflows
Nice to Have
- Master's or PhD in a relevant technical discipline
- Prior work in biopharmaceutical or biomanufacturing settings
- Hands-on experience with bioreactor hardware
- Knowledge of Good Manufacturing Practice (GMP) standards
- Experience with edge computing in lab environments
- Familiarity with Kubernetes for orchestration
- Track record of publishing or presenting technical work
- Exposure to reinforcement learning applications
- Understanding of data privacy in research contexts
- Project leadership in interdisciplinary initiatives
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Hybrid work model with lab presence required
Team
Cross-functional team of biologists, engineers, and data scientists
Technology Stack
- Primary languages: Python, JavaScript
- Frameworks: TensorFlow, PyTorch, Scikit-learn
- Data tools: Pandas, NumPy, Kafka
- Infrastructure: AWS, Docker, Kubernetes
- Lab interfaces: OPC-UA, Modbus, REST APIs
Impact Goals
- Reduce manual intervention in bioreactor operations by 40%
- Increase batch consistency through adaptive control
- Cut development cycle time for new processes
- Enable autonomous fault detection and response
- Scale AI solutions across multiple reactor types
Available for qualified candidates
