Develop and maintain software solutions to integrate laboratory informatics systems with automated hardware systems and robotic laboratory equipment.
Automate workflows related to sample management, inventory tracking, assay preparation, and data analytics.
Collaborate with scientists and engineers to understand requirements and translate them into efficient software solutions.
Legacy System Modernization
Assess existing systems, recommending and implementing modernization strategies that improve functionality, scalability, and ease of maintenance.
Utilize modern software frameworks, cloud-based technologies, and AI-driven coding tools, if relevant, to streamline system modernization.
Data Integration and Automation
Develop API-driven integrations and automated workflows connecting laboratory software, hardware, and internal/external databases.
Ensure robust, real-time synchronization of data across various laboratory systems.
Develop APIs and integration layers to connect applications cross different systems (e.g., chemical structure databases, property databases, and regulatory systems).
ML/AI-Ready Data Foundation Development:
Collaborate with computational scientists and data engineers to design and implement an organizational-wide ML-ready data foundation.
Develop tools and pipelines to ensure data is clean, well-structured, and accessible for machine learning and analytics.
Integrate data from diverse sources (e.g., compound registration, inventory tracking, laboratory systems, and external databases) into a unified data infrastructure.
Communication and Collaboration
Work closely with wet-lab scientists, computational scientists, data engineers, and IT team to clearly identify requirements and collaboratively develop solutions.
Provide technical documentation, training, and support to users and stakeholders.
Work closely with the cross-functional colleagues and data engineer to ensure applications are compatible with the organization’s data infrastructure and Single Source of Truth (SSOT) initiatives.
Qualifications
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Automation Engineering, Bioinformatics or a related field.
2-3 years of experience in software development, scripting, or automation-focused roles.
Strong proficiency in programming/scripting languages (eg. Python, Java, SQL, etc.) and experience with RESTful API integration.
Experience in laboratory automation systems and developing integrations involving biological or chemical informatics.
Experience with legacy system modernization and cloud-based solutions.
Strong problem-solving skills and ability to work in a multidisciplinary environment.
Excellent communication and teamwork skills, capable of bridging computational and laboratory teams.
