{"id":3553614,"url":"https://alion.io/job/thermo-fisher-scientific-systems-design-engineer-bioengineering","title":"Systems Design Engineer - Bioengineering","company":{"id":7922,"name":"Thermo Fisher Scientific","domain":"thermofisher.com","url":"https://alion.io/company/thermo-fisher-scientific","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":81,"open_postings":296,"ghost_share":0,"stale_share":0.77,"repost_share":0.003,"time_to_fill_p50_days":31,"computed_at":"2026-11-01T06:10:25Z"}},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pleasanton, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":107800,"max":143800,"currency":"USD","period":"year","gross":null,"usd_annual":143800},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"FMEA","optional":false},{"name":"JMP","optional":false},{"name":"Machine Learning","optional":false},{"name":"MATLAB","optional":false},{"name":"MBSE","optional":false},{"name":"Next-Generation Sequencing","optional":false},{"name":"Python","optional":false},{"name":"qPCR","optional":false},{"name":"SolidWorks","optional":false},{"name":"Verification & Validation","optional":false}],"status":"live","first_seen_at":"2026-10-30T23:47:40Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-01T20:43:34Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Work Schedule\nStandard (Mon-Fri)Environmental Conditions\nOfficeJob Description\nDiscover Impactful Work\nThermo Fisher Scientific’s Genetic Sciences Division develops integrated platforms, instruments, consumables and reagents for research and clinical applications.\nWe 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.\nThe 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.\nLocation\nThis is a fully onsite role based at our Pleasanton, CA facility. Relocation assistance is not provided for this position.\nWhat You’ll Do\nSupport System Definition and Product Development\nCollaborate with customers, scientists, engineers and external partners to understand product and workflow needs.\nTranslate customer and scientific needs into system requirements, specifications and measurable performance targets.\nMaintain traceability among customer needs, system requirements, subsystem requirements and verification evidence.\nContribute to system architecture, interface definition, concept development and technical trade studies.\nEvaluate candidate concepts based on scientific performance, feasibility, throughput, cost, usability and risk.\nSupport products from early feasibility through integration, verification and design transfer.\nBuild, Integrate and Test Systems\nDesign and build prototypes integrating optical, electrical, mechanical, fluidic, biological and software components.\nDevelop test fixtures, automated experiments and data-acquisition methods.\nConduct system integration, testing and troubleshooting of complex instrumentation and consumable workflows.\nDesign experimental plans, perform studies and analyze results using appropriate statistical methods.\nInvestigate failures using root-cause analysis, DOE, FMEA and structured problem-solving.\nProvide clear, data-driven recommendations through reports, presentations and technical discussions.\nContribute to design reviews, risk assessments and product-development documentation.\nApply Models, Data and AI\nDevelop models for process behavior, throughput, performance and system trade-offs.\nApply MBSE practices to connect workflows, requirements, system behavior, interfaces and verification.\nUse Python, MATLAB, R, JMP or comparable tools for modeling, data analysis and visualization.\nApply machine learning and advanced analytics to identify patterns, anomalies and system-performance drivers.\nUse AI-assisted tools to accelerate literature review, concept exploration, coding, experiment design and technical analysis.\nDevelop reproducible analysis pipelines with appropriate version control, documentation and scientific review.\nValidate AI-generated results through independent analysis and experimentation.\nConnect Biology and Engineering\nEvaluate interactions among samples, assays, reagents, consumables, instruments and software.\nSupport genetic-analysis and sample-preparation workflows such as qPCR, dPCR, sequencing or multiomics.\nHelp teams understand sources of biological and technical variability.\nPartner with assay, consumables, systems, automation and V&V teams to improve performance and robustness.\nEnsure engineering decisions reflect complete customer workflows rather than isolated components.\nContribute to development of products for research-use and regulated markets.\nAdvance Automation and Modern Engineering Methods\nIntegrate sensors, microcontrollers, instruments, liquid handlers or robotics into experimental systems.\nDevelop scripts and software tools for instrument control, automated testing and data collection.\nUse CAD, simulation, rapid prototyping and laboratory fabrication to evaluate concepts quickly.\nApply model-based and automated methods to reduce development cycles and physical iteration.\nExplore AI applications in workflow optimization, anomaly detection, predictive modeling and intelligent instruments.\nIntroduce useful new tools and methods while learning from experienced product developers.\nWhat You Bring\nEducation and Experience\nOne of the following combinations:\nPhD in bioengineering, biomedical engineering, chemical engineering, biophysics or a related field, with zero to approximately three years of relevant experience.\nMaster’s degree in a related discipline with approximately two or more years of relevant research or industry experience.\nBachelor’s degree in a related discipline with approximately five or more years of relevant product-development experience.\nAdditional qualifications\nHands-on experience developing experimental systems, prototypes or engineering solutions for biological applications.\nExperience working across scientific and engineering disciplines.\nIndustry experience is valued but not required when academic work demonstrates practical system development and problem-solving.\nTechnical Capabilities\nStrong foundation in bioengineering, molecular biology, biophysics or biological-system development.\nHands-on experience with several of the following:Molecular biology or sample-preparation workflows\nMicrofluidics and fluid handling\nOptical, electrical or mechanical instrumentation\nSensors, data acquisition and instrument control\nRobotics or laboratory automation\nCAD and rapid prototyping\nComputational modeling and simulation\nStatistics, machine learning or AI\n\nExperience with systems-engineering practices, including requirements, interfaces, risk analysis and V&V.\nFamiliarity with DOE, RCA, FMEA and statistical analysis.\nProficiency with tools such as Python, MATLAB, JMP, R, LabVIEW, SolidWorks or comparable platforms.\nExperience with qPCR, dPCR, CE/Sanger sequencing, microarray, NGS, DNA synthesis or related workflows is preferred.\nBehaviors\nHands-on builder who learns through experiments, prototypes and data.\nCurious across biology, engineering, software and emerging technology.\nHighly data-driven and attentive to system-level effects.\nComfortable working through ambiguity and complex technical problems.\nBuilds credibility and collaborative relationships across disciplines.\nCommunicates technical results clearly in writing and presentations.\nMoves quickly while maintaining scientific rigor and reproducibility.\nUses AI ambitiously while validating results through sound engineering judgment.\nWhy This Role Matters\nThe 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.\n Compensation and Benefits\nThe 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:\nA choice of national medical and dental plans, and a national vision plan, including health incentive programs\n\nEmployee assistance and family support programs, including commuter benefits and tuition reimbursement\n\nAt 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\n\nRetirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan\n\nEmployees’ Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount\n\nFor more information on our benefits, please visit: 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