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Staff Engineer, Systems Design - Automation Integration

Thermo Fisher Scientific

Singapore, SingaporeFull TimeStaffH-1B sponsor company
Sign in to applyVerified
Location
Singapore, Singapore
Employment
Full Time
Work model
On-Site
Level
Staff
H-1B history
76 approvals (FY2023)
Posted

About this role

Work Schedule Standard (Mon-Fri) Environmental Conditions Office Job Description About the Role Thermo Fisher Scientific’s Genetic Sciences Division is expanding its capabilities in automated, connected and AI-enabled laboratory workflows. We are seeking a Staff Engineer in Laboratory Automation & Systems Integration to develop solutions connecting GSD instruments and consumables with robots, liquid handlers, workflow software and laboratory data systems. This individual will architect integrations, build and test working systems, and demonstrate complete genomic workflows to customers and partners. The successful candidate will combine hands-on automation experience with strong systems thinking and an understanding of genomic workflows in biopharma. This person will translate customer needs into scalable, reusable product capabilities—not isolated custom integrations. What You’ll Do Architect and Integrate Automated Workflows Develop workflows integrating instruments, consumables, assays, robots, liquid handlers, software and data. Translate customer use cases into system requirements, interfaces and automation concepts. Define physical, mechanical, electrical, communications and software interfaces. Develop instrument-control APIs, device drivers, protocols and workflow abstractions. Build prototypes and integrated systems to evaluate concepts and partner technologies. Design for scheduling, synchronization, sample traceability, error recovery, safety and unattended operation. Create reusable integration patterns that scale across products, customers and automation platforms. Test and Demonstrate Customer Solutions Build and execute end-to-end automated workflows representing biopharma and genomic applications. Develop integration-test strategies covering normal operation, edge cases, recovery and extended unattended use. Evaluate throughput, reliability, sample integrity, contamination control and data traceability. Lead technical demonstrations for customers, partners and internal stakeholders. Support customer evaluations, early-access programs and selected integration deployments. Translate testing and customer feedback into product requirements and integration improvements. Develop and maintain system requirements, interface specifications, architecture definitions and verification plans, ensuring traceability from customer needs through system verification. Understand Customer Science and Workflows Partner with customers to understand laboratory processes, constraints and automation priorities. Develop workflows involving sample preparation, nucleic-acid processing, qPCR, dPCR and related genomic-analysis steps. Understand automation needs across biopharma research, screening, process development and quality workflows. Partner with assay, consumables, instrument and software teams to improve automation readiness. Balance throughput, flexibility, walk-away time, usability, reliability and cost. Ensure solutions protect sample identity, integrity and chain of custody. Build Automation Vendor and Partner Relationships Develop technical partnerships with robotics, liquid-handling, automation-software and integration companies. Maintain knowledge of leading vendors, platforms, technologies and interface standards. Understand partner architectures, product needs, development constraints and support models. Evaluate partners based on technical compatibility, scalability, reliability and business value. Lead joint interface definition, integration planning, testing and problem resolution. Convert partner learning into reusable standards and product requirements. Advance Intelligent and AI-Enabled Automation Develop Lab-of-the-Future and automated sample-to-answer capabilities. Contribute to Lab-in-the-Loop systems using experimental data and real-time feedback to optimize workflows. Apply AI to scheduling, anomaly detection, recovery, predictive maintenance and workflow optimization. Use AI-assisted engineering to

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