Systems Design Engineer - Bioengineering

ThermoFisher Scientific; Pleasanton (CA); On-site; USD 108,000 - 144,000; Full time

Benefits offered by this job

Medical and dental plans

Vision plan

401(k) plan with company match

Employee stock purchase plan

Job summary

Thermo Fisher Scientific’s Genetic Sciences Division seeks an early-career Bioengineer to develop next-generation genetic-analysis platforms, multiomics workflows and automated scientific systems. You will build prototypes, design experiments, and integrate technologies while using data-driven approaches to solve multidisciplinary problems.

The role emphasizes computational modeling, automation and AI, collaborating with experienced scientists and engineers to define architecture, verify systems

Qualifications

• Hands-on experience developing experimental systems, prototypes or engineering solutions for biological applications.
• Experience working across scientific and engineering disciplines.
• Industry experience is valued but not required when academic work demonstrates practical system development.

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.
• Maintain traceability among customer needs, system requirements, subsystem requirements and verification evidence.
• Contribute to system architecture, interface definition, concept development and technical trade studies.
• Evaluate candidate concepts based on 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.
• Conduct system integration, testing and troubleshooting of complex instrumentation and consumable workflows.
• Design experimental plans, perform studies and analyze results using appropriate statistical methods.
• Investigate failures using root-cause analysis, DOE, FMEA and structured problem-solving.
• Provide clear, data-driven recommendations through reports, presentations and technical discussions.
• Contribute to design reviews, risk assessments and product-development documentation.
• Develop models for process behavior, throughput, performance and system trade-offs.
• Apply MBSE practices to connect workflows, requirements, system behavior, interfaces and verification.
• Use Python, MATLAB, R, JMP or comparable tools for modeling, data analysis and visualization.
• Apply machine learning and advanced analytics to identify patterns, anomalies and system-performance drivers.
• Use AI-assisted tools to accelerate literature review, concept exploration, coding, experiment design and technical analysis.
• Develop reproducible analysis pipelines with appropriate version control, documentation and scientific review.
• Validate AI-generated results through independent analysis and experimentation.

Skills

Systems engineering

Data analysis

Python

MATLAB

Statistics

Machine learning

DOE methods

AI tools

Education

PhD in bioengineering / related field

MS in related discipline

Bachelor's degree in related discipline

Tools

LabVIEW

SolidWorks

JMP

R

CAD

Job description

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

Discover Impactful Work

Thermo Fisher Scientific’s Genetic Sciences Division develops integrated platforms, instruments, consumables and reagents for research and clinical applications.

We are seeking an early-career Bioengineer to help develop next-generation genetic-analysis, multiomics and automated scientific workflows. This is a hands-on systems role for someone who enjoys building prototypes, designing experiments, integrating technologies and using data to solve multidisciplinary problems.

The successful candidate will bring modern capabilities in computational modeling, automation, data science and AI. Working with experienced scientists and engineers, this person will contribute to system definition, architecture, integration and verification across instruments, consumables, assays, software and data.

Location

This is a fully onsite role based at our Pleasanton, CA facility. Relocation assistance is not provided for this position.

What You’ll Do

Support System Definition and Product Development

• 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.

• Maintain traceability among customer needs, system requirements, subsystem requirements and verification evidence.

• Contribute to system architecture, interface definition, concept development and technical trade studies.

• Evaluate candidate concepts based on scientific performance, feasibility, throughput, cost, usability and risk.

• Support products from early feasibility through integration, verification and design transfer.

Build, Integrate and Test Systems

• Design and build prototypes integrating optical, electrical, mechanical, fluidic, biological and software components.

• Develop test fixtures, automated experiments and data-acquisition methods.

• Conduct system integration, testing and troubleshooting of complex instrumentation and consumable workflows.

• Design experimental plans, perform studies and analyze results using appropriate statistical methods.

• Investigate failures using root-cause analysis, DOE, FMEA and structured problem-solving.

• Provide clear, data-driven recommendations through reports, presentations and technical discussions.

• Contribute to design reviews, risk assessments and product-development documentation.

Apply Models, Data and AI

• Develop models for process behavior, throughput, performance and system trade-offs.

• Apply MBSE practices to connect workflows, requirements, system behavior, interfaces and verification.

• Use Python, MATLAB, R, JMP or comparable tools for modeling, data analysis and visualization.

• Apply machine learning and advanced analytics to identify patterns, anomalies and system-performance drivers.

• Use AI-assisted tools to accelerate literature review, concept exploration, coding, experiment design and technical analysis.

• Develop reproducible analysis pipelines with appropriate version control, documentation and scientific review.

• Validate AI-generated results through independent analysis and experimentation.

Connect Biology and Engineering

• Evaluate interactions among samples, assays, reagents, consumables, instruments and software.

• Support genetic-analysis and sample-preparation workflows such as qPCR, dPCR, sequencing or multiomics.

• Help teams understand sources of 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 rather than isolated components.

• Contribute to development of products for research-use and regulated markets.

Advance Automation and Modern Engineering Methods

• 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 quickly.

• Apply model-based and automated methods to reduce development cycles and physical iteration.

• Explore AI applications in workflow optimization, anomaly detection, predictive modeling and intelligent instruments.

• Introduce useful new tools and methods while learning from experienced product developers.

What You Bring

Education and Experience

One of the following combinations:

• PhD in bioengineering, biomedical engineering, chemical engineering, biophysics or a related field, with zero to approximately three years of relevant experience.

• Master’s degree in a related discipline with approximately two or more years of relevant research or industry experience.

• Bachelor’s degree in a related discipline with approximately five or more years of relevant product-development experience.

Additional qualifications

• Hands-on experience developing experimental systems, prototypes or engineering solutions for biological applications.

• Experience working across scientific and engineering disciplines.

• Industry experience is valued but not required when academic work demonstrates practical system development and problem-solving.

Technical Capabilities

• Strong foundation in bioengineering, molecular biology, biophysics or biological-system development.

• Hands-on experience with several of the following:

• Molecular biology or sample-preparation workflows

• Microfluidics and fluid handling

• Optical, electrical or mechanical instrumentation

• Sensors, data acquisition and 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 V&V.

• Familiarity with DOE, RCA, FMEA and statistical analysis.

• Proficiency with tools such as Python, MATLAB, JMP, R, LabVIEW, SolidWorks or comparable platforms.

• Experience with qPCR, dPCR, CE/Sanger sequencing, microarray, NGS, DNA synthesis or related workflows is preferred.

Behaviors

• Hands-on builder who learns through experiments, prototypes and data.

• Curious across biology, engineering, software and emerging technology.

• Highly data-driven and attentive to system-level effects.

• Comfortable working through ambiguity and complex technical problems.

• Builds credibility and collaborative relationships across disciplines.

• Communicates technical results clearly in writing and presentations.

• Moves quickly while maintaining scientific rigor and reproducibility.

• Uses AI ambitiously while validating results through sound engineering judgment.

Why This Role Matters

The next generation of life-science platforms will be developed by engineers who can connect biology, instrumentation, consumables, automation, computation and AI. This role will bring modern capabilities and new perspectives into GSD while developing future technical talent through hands‑on product development.

Compensation and Benefits

The salary range estimated for this position based in California is $107,800.00–$143,800.00.

This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy. We offer a comprehensive Total Rewards package that our U.S. colleagues and their families can count on, which includes:

• A 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 paid time off (PTO), 10 paid holidays annually, paid parental leave (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

• Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan

• Employees’ Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount

For more information on our benefits, please visit: https://jobs.thermofisher.com/global/en/total-rewards

Thermo Fisher Scientific is an EEO/Affirmative Action Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other legally protected status.