Systems Design Engineer - Bioengineering

Thermo Fisher Scientific • Pleasanton, CA

4d • Onsite

About The Position

Thermo Fisher Scientific’s Genetic Sciences Division develops integrated platforms, instruments, consumables and reagents for research and clinical applications. The Systems Design Engineer will be an early-career bioengineer contributing to next-generation genetic-analysis, multiomics and automated scientific workflows. This hands-on systems role involves building prototypes, designing experiments, integrating technologies and applying data-driven methods to multidisciplinary problems.

Working with experienced scientists and engineers, the engineer will contribute to system definition, architecture, integration and verification across instruments, consumables, assays, software and data. The role supports product development from early feasibility through integration, verification and design transfer, and combines biological workflows with instrumentation, automation, computational modeling, data science and AI. The position is fully onsite at the Pleasanton, California facility; relocation assistance is not provided.

Requirements

• A PhD in bioengineering, biomedical engineering, chemical engineering, biophysics or a related field, with zero to approximately three years of relevant experience; or a related master’s degree with approximately two or more years of relevant research or industry experience; or a related bachelor’s degree with approximately five or more years of relevant product-development experience.
• Hands-on experience developing experimental systems, prototypes or engineering solutions for biological applications.
• Experience working across scientific and engineering disciplines.
• A strong foundation in bioengineering, molecular biology, biophysics or biological-system development.
• Hands-on experience with several relevant areas, such as molecular biology or sample preparation, microfluidics and fluid handling, instrumentation, sensors and data acquisition, instrument control, robotics or laboratory automation, CAD and rapid prototyping, computational modeling and simulation, statistics, machine learning or AI.
• Experience with systems-engineering practices, including requirements, interfaces, risk analysis and verification and validation.
• Familiarity with DOE, root-cause analysis, FMEA and statistical analysis.
• Proficiency with tools such as Python, MATLAB, JMP, R, LabVIEW, SolidWorks or comparable platforms.
• Ability to communicate technical results clearly in writing and presentations, collaborate across disciplines, and work through ambiguity and complex technical problems.
• A data-driven, hands-on approach, with attention to scientific rigor, reproducibility and validation of AI-generated results.

Nice To Haves

• Experience with qPCR, dPCR, CE/Sanger sequencing, microarray, NGS, DNA synthesis or related workflows is preferred.
• Industry experience is valued but not required when academic work demonstrates practical system development and problem-solving.

Responsibilities

• Collaborate with customers, scientists, engineers and external partners to understand product and workflow needs.
• Translate customer and scientific needs into system requirements, specifications and measurable performance targets, and maintain traceability through verification evidence.
• Contribute to system architecture, interface definition, concept development and technical trade studies; assess concepts for scientific performance, feasibility, throughput, cost, usability and risk.
• Support products from early feasibility through integration, verification and design transfer.
• Design and build prototypes integrating optical, electrical, mechanical, fluidic, biological and software components.
• Develop test fixtures, automated experiments and data-acquisition methods; integrate, test and troubleshoot complex instrumentation and consumable workflows.
• Design experimental plans, conduct studies and analyze results using suitable statistical methods.
• Investigate failures using root-cause analysis, DOE, FMEA and structured problem-solving.
• Communicate data-driven recommendations through reports, presentations and technical discussions, and contribute to design reviews, risk assessments and product-development documentation.
• Develop models for process behavior, throughput, performance and system trade-offs; apply MBSE to connect workflows, requirements, behavior, interfaces and verification.
• Use computational and statistical tools for modeling, data analysis and visualization; apply machine learning and advanced analytics to identify patterns, anomalies and performance drivers.
• Use AI-assisted tools for literature review, concept exploration, coding, experiment design and technical analysis, while validating generated results through independent analysis and experimentation.
• Develop reproducible analysis pipelines with suitable version control, documentation and scientific review.
• Evaluate interactions among samples, assays, reagents, consumables, instruments and software, and support genetic-analysis and sample-preparation workflows.
• Help teams understand biological and technical variability; partner with assay, consumables, systems, automation and V&V teams to improve performance and robustness.
• Ensure engineering decisions reflect complete customer workflows and contribute to products for research-use and regulated markets.
• Integrate sensors, microcontrollers, instruments, liquid handlers or robotics into experimental systems.
• Develop scripts and software tools for instrument control, automated testing and data collection.
• Use CAD, simulation, rapid prototyping and laboratory fabrication to evaluate concepts; apply model-based and automated methods to reduce development cycles and explore AI applications in workflow optimization, anomaly detection, predictive modeling and intelligent instruments.

Benefits

• Choice of national medical and dental plans and a national vision plan, including health incentive programs.
• Employee assistance and family support programs, including commuter benefits and tuition reimbursement.
• At least 120 hours of paid time off and 10 paid holidays annually.
• Paid parental leave, including 3 weeks for bonding and 8 weeks for caregiver leave.
• Accident and life insurance, and short- and long-term disability in accordance with company policy.
• Competitive 401(k) U.S. retirement savings plan.
• Employees’ Stock Purchase Plan, with eligible colleagues able to purchase company stock at a discount.
• The position may be eligible for a variable annual bonus based on company, team and/or individual performance results in accordance with company policy.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level