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Biomedical engineers

Official title Bioengineers and Biomedical Engineers (SOC 17-2031)

Also called Bioengineer, Medical device engineer, R&D engineer medical devices, Clinical engineer, Biomechanical engineer

In brief

In May 2025, BLS counted 23,480 US biomedical engineers, with median pay of $109,370 a year. Of the BLS counts since 2021, the May 2025 count is the highest. The earliest figure here is an estimate of 2,000 from 1970, not measured the same way as today's count. The last full technology era for biomedical engineers: Multi-material additive manufacturing, 2015 to 2023.

What the sources say

Official outlook

BLS projects employment to grow 7.6% from 2025 to 2035.

BLS Employment Projections 2025-35

AI exposure studies

Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. BLS publishes these counts as yearly survey snapshots and cautions against reading them as a precise trend.

Last updated .

Cite this page
APA

Future History. (2026, October 11). Biomedical engineers: jobs and pay since 1970 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/17-2031

Chicago

Future History. "Biomedical engineers: jobs and pay since 1970." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/17-2031.

BibTeX

@misc{futurehistory_17_2031, author = {{Future History}}, title = {Biomedical engineers: jobs and pay since 1970}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/17-2031}}, note = {Last updated 2026-10-11. Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35}, }

The access date is today's date on your device.

drag to travel through time
195019752000now
2026
Known then as Medical Electronics Engineer / Clinical Engineer (pre-professional era)
Known then as Biomedical Engineer (emerging profession, NIH-funded academic era)
Known then as Biomedical Engineers (BLS SOC 17-2031, first listed in OOH)
Known then as Bioengineers and Biomedical Engineers (BLS SOC 17-2031, 2018 SOC revision)
Known today as Bioengineers and Biomedical Engineers (BLS SOC 17-2031, 2018 SOC revision)
Projected to still be called Bioengineers and Biomedical Engineers (BLS SOC 17-2031, 2018 SOC revision)
Data from the May 2025 survey
US Employment
23K
Est.

Stated in source: BLS OEWS

Official statistic
Report an error
Median Annual Wage
$109,370

≈ $106,566 in 2024 prices (derived by us, CPI-adjusted)

Official statistic
Report an error
Beat · 1948

Work on the first heart-lung machines begins in earnest in 1948, with Willem Kolff bringing hemodialysis to the United States (Cleveland Clinic, 1950). The first inter-society engineering meeting focused on engineering in medicine is held around 1948. These two threads -- life-sustaining artificial organs and the institutional recognition of engineering in clinical settings -- mark the practical origin year of the profession. No formal BME degree or title existed yet; the people doing this work called themselves electrical engineers or physicists or physiologists.

Beat · 1953

John H. Gibbon Jr. performs the first successful open-heart surgery assisted by a heart-lung machine at Jefferson Medical College, Philadelphia. The machine, developed over 23 years, oxygenated blood outside the patient's body for 26 minutes while Gibbon repaired an atrial septal defect. This is probably the first successful example of a device designed and built by what we would now call a biomedical engineer being used to sustain human life in surgery.

Beat · 1968

The Biomedical Engineering Society is incorporated in Illinois on February 1, 1968, with 171 founding members and 89 charter members. Its inaugural meeting is held at the Ritz-Carlton Hotel in Atlantic City on April 17, 1968 in cooperation with the Federation of American Societies for Experimental Biology. The founding charter emphasized equal status for engineering and biomedical perspectives -- the persistent tension in a field that requires depth in both. In the same year, Case Western Reserve, University of Virginia, Johns Hopkins, and Duke establish dedicated biomedical engineering departments.

Beat · 1976

The Medical Device Amendments of 1976 create the modern FDA medical device regulatory framework: the 510(k) substantial-equivalence pathway for class II devices and the PMA (Premarket Approval) pathway for class III high-risk devices. This regulatory architecture creates a permanent demand driver for biomedical engineers: every new device requires documented design verification, biocompatibility testing, and a technical file that a licensed engineer must sign. The 1976 amendments are probably the single most important labor-market factor in the profession's long-term employment stability.

Beat · 1975

The Whitaker Foundation is established from the $60 million bequest of U.A. Whitaker, supplemented by $37 million from his wife Helen upon her death in 1982. Over its 30-year lifespan (closed June 30, 2006), the foundation invested over $700 million to establish more than 75 biomedical engineering departments, fund close to 1,500 faculty members, and train over 400 graduate fellows. Whitaker-funded faculty generated 278 patents, founded more than 100 companies, and invented more than 200 significant products. This is the most consequential private investment in building a single engineering profession in American history.

Beat · 2000

NIH establishes the National Institute of Biomedical Imaging and Bioengineering (NIBIB) as the federal home for bioengineering research, giving the field a permanent institutional funding base at the NIH level. In the same year, BLS first lists biomedical engineers as a distinct occupational category in the Occupational Outlook Handbook, citing approximately 7,200 practitioners and projecting 31% growth over the following decade. The OOH listing marks the profession's formal recognition in the US federal labor classification system.

Beat · 2018

BLS updates the Standard Occupational Classification to rename the occupation from "Biomedical Engineers" to "Bioengineers and Biomedical Engineers" (SOC 17-2031 retained). The change reflects the broadening of the profession beyond clinical medical devices into synthetic biology, tissue engineering, computational biology, and bioinformatics -- areas where the practitioner's primary domain is biological systems engineering rather than the design of FDA-regulated devices. The renamed occupation now spans practitioners at both extremes: clinical device engineers navigating FDA 510(k) submissions and bench-to-bedside device development, and computational bioengineers writing machine learning models for genomic data at health technology companies.

How to read this number

OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.

Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.

Official statistic: Copied by a script from a statistics agency table or a published study's table, not retyped by hand. BLS figures and the forecast and exposure tables are also re-checked against that table on every data run. Researched context: Researched from the cited source rather than copied from it by a script, so it is not machine-checked yet. Spot a mistake? Each figure has a “Report an error” link.

Cited forecasts · present → 2035

Will AI replace biomedical engineers? What the research says

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, we show the disagreement rather than an average.

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, the spread is the honest signal.

What published forecasts say
Forecast change in the number of people doing this work, as published by each named source. Bars share one scale on every role, centred on zero and reaching the end at ±30%. Grey marks a small change, 3% or less either way.
BLS Employment Projections 2025-35
→ 2035
+7.6%
BLS National Employment Matrix, 2025-35 cycle, line for SOC 17-2031 (Bioengineers and biomedical engineers): 23.8 thousand jobs in 2025, projected 25.7 thousand in 2035, a change of +1.8 thousand (+7.6%). Matrix employment counts all jobs in the occupation, including self-employed workers. The average for all occupations in this cycle is +3.5%.
Official statisticReport an error
How exposed is this work to AI (research measures)
Scores as published by each study. Each row says what it measures. These measure what AI could technically do, not forecasts of jobs lost.
Eloundou et al. (2023), "GPTs are GPTs"
2023 study · Share of tasks exposed to LLMs (β, human-rated)
53.8%
of tasks
What this measures

Published occupation-level exposure from the paper's occ_level.csv for O*NET-SOC 17-2031.00 Bioengineers and Biomedical Engineers. Shown: human-rated β = 0.538, the share of the occupation's tasks an LLM could do in at least half the time at equal quality, counting tasks that need LLM-powered software at half weight (β = E1 + 0.5 × E2). Other published measures for this occupation: human-rated α (LLM alone) 0.256 and γ (all LLM-assisted) 0.821; GPT-4-rated β 0.59. This measures how much of the work an LLM could touch, not how many jobs disappear.

Official statisticReport an error
Today, in this role

What's changing day to day for biomedical engineers

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is sitting alongside you hereExecute biofluid dynamics and structural biomechanics simulations for implant and device design: using Ansys SimAI surrogate models trained on prior finite-element datasets to predict pressure distributions in cardiovascular stents, stress concentrations in orthopedic fixation hardware, or fatigue life in spinal implants 10–100x faster than full-solver runs

Execute biofluid dynamics and structural biomechanics simulations for implant and device design: using Ansys SimAI surrogate models trained on prior finite-element datasets to predict pressure distributions in cardiovascular stents, stress concentrations in orthopedic fixation hardware, or fatigue life in spinal implants 10–100x faster than full-solver runs; gate acceptance on SimAI confidence scores; run verification solver checks when geometry departs from training distribution before submitting results to design review.[10],[4]

Tools picking this up
Where your edge is

SimAI confidence scores flag when implant geometry is outside the training distribution and the surrogate prediction should not be trusted for regulatory use. Build a verification discipline: document which design-variant families are covered by your surrogate training set, and apply mandatory full-solver re-runs for any geometry outside that envelope. FDA design controls require that verification methods be validated: maintain records that trace each AI-accelerated simulation to the underlying verified solver methodology it approximates.

AI is sitting alongside you hereConduct AI-assisted systematic literature review for Clinical Evaluation Reports (CER) required under EU MDR 2017/745 or FDA 510(k) substantial equivalence arguments: using Elicit to query the biomedical literature at scale, surface relevant clinical studies, safety data, and performance benchmarks for the device type and indication

Conduct AI-assisted systematic literature review for Clinical Evaluation Reports (CER) required under EU MDR 2017/745 or FDA 510(k) substantial equivalence arguments: using Elicit to query the biomedical literature at scale, surface relevant clinical studies, safety data, and performance benchmarks for the device type and indication; critically appraising AI-retrieved evidence for methodological quality; synthesizing findings into the structured CER narrative with full citation provenance.[13],[14]

Tools picking this up
Where your edge is

Elicit can retrieve and summarize hundreds of relevant clinical papers in a fraction of the time required for manual PubMed search, but the critical appraisal step (assessing study quality, patient population applicability, and follow-up duration relevance for your specific device category) requires clinical engineering expertise that the tool cannot provide. EU MDR's MEDDEV 2.7/1 Rev 4 guidance requires the engineer to demonstrate systematic literature appraisal methodology; AI-assisted retrieval must be paired with a documented appraisal protocol and human critical review for submissions to pass notified body scrutiny.

AI is sitting alongside you hereAnalyze medical imaging datasets for device performance evaluation and clinical evidence generation: using NVIDIA Clara imaging AI pipelines to process CT, MRI, or X-ray series at scale, measuring device positioning accuracy, radiopacity artifact extent, or implant subsidence over time across patient cohorts

Analyze medical imaging datasets for device performance evaluation and clinical evidence generation: using NVIDIA Clara imaging AI pipelines to process CT, MRI, or X-ray series at scale, measuring device positioning accuracy, radiopacity artifact extent, or implant subsidence over time across patient cohorts; curating AI-extracted measurements into structured datasets for regulatory submissions and peer-reviewed clinical papers.[7],[12]

Tools picking this up
Where your edge is

NVIDIA Clara's imaging AI can process hundreds of CT or MRI series that would take weeks to analyze manually, but the engineer must define the measurement protocol, validate that the AI measurements agree with expert human raters on a representative calibration set, and report any systematic bias in the AI tool's output in the regulatory submission. Build competency in medical image quality assessment and statistical agreement analysis (intraclass correlation, Bland-Altman) so you can credibly validate and report AI-assisted measurement data to FDA reviewers.

Where biomedical engineers go next

Natural next steps for someone with your foundation: not exits, evolutions.

What each move takes

A direction you could grow

Architectural and Engineering Managers

Senior biomedical engineers who develop regulatory program management, team leadership, and vendor governance skills are well-positioned to move into Engineering Manager roles at medical device companies. This transition is especially valuable as organizations navigate the rapid expansion of AI-assisted design and regulatory tooling, deciding which QMS AI platforms (Greenlight Guru, MasterControl AI) to invest in, setting review standards for AI-generated device documentation, and building team capability in AI-augmented regulatory workflows. Engineering Managers in medical devices retain full regulatory accountability and technical credibility while operating at program scope (budget, headcount, submission timelines) where AI displacement pressure is minimal. BLS projects sustained demand for engineering managers tied to healthcare technology investment.

What you'd add
· AI tool evaluation and governance in regulated contexts: building team review standards for AI-generated design documents and risk management outputs per FDA Design Controls
· People management: hiring biomedical engineers, conducting performance reviews, career development coaching in a regulated industry context
· Executive communication: translating device clinical risk, regulatory timeline risk, and design failure modes into portfolio-level business impact for non-technical leadership
What it takesSome new skills to pick up
Tools of the era

How has the work of biomedical engineers changed since 1948?

The tools that defined the work, one line per era. Select an era to see how it reshaped the work.

  • Bench instruments and analog electronics (oscilloscope, galvanometer, analog signal processing)

    The founding generation of biomedical engineers worked with bench electronics: oscilloscopes, vacuum-tube amplifiers, galvanometers, and strip-chart recorders. Measuring a cardiac signal required building a custom amplifier from components; designing a prosthetic limb meant manual stress-calculation at a drafting table. The engineer's bench was indistinguishable from that of any electrical or mechanical engineer of the era; what distinguished the biomedical practitioner was the application, not the tools. Earl Bakken built the first transistorized pacemaker in 1957 on a workbench in his garage using commercially available transistors and a circuit described in an electronics hobbyist magazine.

  • Formalized academic programs and early institutional computing (departmental PDP minicomputers, FORTRAN simulation)

    The formation of dedicated biomedical engineering departments at Virginia, Case Western Reserve, Johns Hopkins, and Duke in 1967-1968 transformed the profession from a collection of self-taught hybrids into a credentialed engineering discipline. Graduate students gained access to departmental PDP minicomputers and began writing FORTRAN simulations of physiological systems: blood flow through a stenotic vessel, electrode-tissue impedance, bone remodeling under cyclic load. The computing was slow and expensive by later standards, but the key shift was conceptual: biomedical engineers now built mathematical models of biological systems rather than simply building physical devices. Finite element analysis for implant stress distribution, performed on mainframes or minicomputers and requiring weeks to run, became a standard part of the implant design process by the late 1970s.

    Effect on the work

    The Whitaker Foundation, founded in 1975, began investing in biomedical engineering departments that year, eventually funding many departments and training roughly 1,500 faculty members. The faculty wave created the supply pipeline for the profession's 1990s and 2000s workforce growth.

  • CAD / FEA workstations, MRI and CT post-processing, early biomaterials informatics (AUTOCAD, Pro/ENGINEER, ANSYS)

    The mid-1980s brought desktop CAD workstations into biomedical engineering labs. Pro/ENGINEER (1987) and later SolidWorks (1995) gave implant designers parametric 3D modeling that replaced hand drafting and simplified design iteration. ANSYS finite element analysis moved from mainframes to Unix workstations and became a standard tool for validating orthopedic implant stress distributions before any material was machined. Simultaneously, CT and MRI scanners were generating digital volumetric datasets that biomedical engineers could post-process: the first patient-specific surgical implant sizing computations, femoral prosthetic fit optimizations using CT cross-sections, and cochlear implant electrode trajectory planning all emerged in this era. The regulatory environment kept pace: FDA's 510(k) substantial-equivalence pathway, created by the 1976 Medical Device Amendments, matured through the 1980s and began requiring documented engineering design verification that only trained biomedical engineers could produce.

    Effect on the work

    CAD and FEA adoption reduced the time to design and verify an implant geometry from months to weeks, enabling smaller teams to run more design iterations. However, the regulatory documentation burden (Design History File, risk management per ISO 14971, biocompatibility per ISO 10993) expanded in parallel, absorbing the productivity gains and maintaining headcount. The net effect on the workforce was moderate growth rather than displacement.

  • Genomics informatics platforms, digital pathology, rapid prototyping / additive manufacturing (SLA, FDM for medical models)

    The Human Genome Project, completed in 2003, opened a new domain for biomedical engineers: bioinformatics and genomics instrumentation. Affymetrix microarray scanners, Illumina sequencing platforms, and flow cytometers all required biomedical engineers to design the optical, fluidic, and signal-processing systems that generated genomic data. Simultaneously, the first clinical-grade 3D printing systems (Stratasys FDM, stereolithography, selective laser sintering) arrived in hospital engineering departments for anatomical model fabrication, presurgical planning, and custom orthotic production. Rapid prototyping shortened the design-test-iterate cycle for device concepts from months to days. NIH established the National Institute of Biomedical Imaging and Bioengineering in 2000, creating a dedicated federal funding home for the field.

    Effect on the work

    The genomics instrumentation and digital pathology market created an entirely new subspecialty of biomedical engineering focused on optical systems and microfluidics, helping employment more than double between 2000 and 2010 as the genomics industry scaled.

  • Multi-material additive manufacturing, nTop implicit modeling, cloud-based QMS platforms (Greenlight Guru, MasterControl)

    Selective laser melting and electron beam melting of titanium alloys entered FDA-cleared orthopedic implant production in the mid-2010s, enabling porous lattice structures that promote bone ingrowth in ways impossible with machined implants. Tools like nTop (formerly nTopology) gave biomedical engineers a dedicated platform for designing these complex geometries using implicit modeling rather than the mesh-based CAD that conventional tools relied on. Simultaneously, cloud-based quality management systems specifically designed for FDA 21 CFR 820 Design Controls and ISO 13485 emerged: Greenlight Guru (founded 2013), Arena Solutions, and MasterControl shifted design control documentation from paper and generic spreadsheets to purpose-built regulatory workflow platforms. These tools accelerated 510(k) submission preparation but also raised the bar for documentation completeness that FDA reviewers expected.

  • AI-accelerated simulation, generative geometry, and LLM-assisted regulatory document drafting (Ansys SimAI, NVIDIA Clara, Elicit, Greenlight Guru AI)

    The 2023-2026 AI tool wave reached biomedical engineering through several channels simultaneously. Ansys SimAI surrogate modeling (generally available 2024, restructured under Synopsys as Ansys 2026 R1) enables physics predictions for cardiac flow, implant stress, and electrode field distributions at 10-100 times the speed of full finite-element solves, compressing design iteration cycles that previously took days into minutes. NVIDIA Clara's imaging AI platform processes CT, MRI, and pathology datasets at scale for device performance measurement studies and clinical evidence generation. Elicit and Consensus enable AI-assisted systematic literature review for Clinical Evaluation Reports required under FDA 510(k) submissions and EU MDR 2017/745. Greenlight Guru's AI layer surfaces open design control obligations, populates risk management worksheets, and drafts 510(k) technical file sections. The common thread is augmentation, not substitution: FDA Design Controls under 21 CFR 820 and ISO 13485 require a licensed, accountable engineer to approve every design output -- the AI accelerates the work but cannot sign off on it. BLS's growth projection for 2024-2034 reflects this dynamic: the field is growing despite AI adoption because the human accountability requirement scales with device complexity, not against it.

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Bioengineers and Biomedical Engineers employment and pay by year

On record since1948
Latest US employment23,480 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Latest US median pay$109,370 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Outlook+7.6% by 2035Source: BLS Employment Projections 2025-35Official statisticReport an error
View all 26 years of cited US data, each linked to its source
YearUS employmentAnnual pay (median unless marked)SourceReport
19702,000n/aEst., Clinical engineering - Wikipedia Researched contextReport
19804,000n/aEst., Whitaker Foundation and biomedical… Researched contextReport
20006,600$57,480BLS OEWS 2000 Official statisticReport
20036,980$63,660BLS OEWS May 2003 Official statisticReport
20048,650$67,690BLS OEWS May 2004 Official statisticReport
200511,660$71,840BLS OEWS May 2005 Official statisticReport
200614,030$73,930BLS OEWS May 2006 Official statisticReport
200715,400$75,440BLS OEWS May 2007 Official statisticReport
200815,220$77,400BLS OEWS May 2008 Official statisticReport
200914,760$78,860BLS OEWS May 2009 Official statisticReport
201015,280$81,540BLS OEWS May 2010 (employment) Official statisticBLS OEWS 2010 (pay) Official statisticReport
201116,590$84,670BLS OEWS May 2011 Official statisticReport
201218,810$86,960BLS OEWS May 2012 Official statisticReport
201319,890$88,670BLS OEWS May 2013 Official statisticReport
201420,080$86,950BLS OEWS May 2014 Official statisticReport
201520,890$86,220BLS OEWS May 2015 Official statisticReport
201620,590$85,620BLS OEWS May 2016 Official statisticReport
201720,100$88,040BLS OEWS May 2017 Official statisticReport
201818,970$88,550BLS OEWS May 2018 Official statisticReport
201919,780$91,410BLS OEWS May 2019 Official statisticReport
202018,660$92,620BLS OEWS May 2020 Official statisticReport
202117,190$97,410BLS OEWS May 2021 Official statisticReport
202219,210$99,550BLS OEWS May 2022 Official statisticReport
202319,320$100,730BLS OEWS May 2023 Official statisticReport
202421,860$106,950BLS OEWS May 2024 (employment) Official statisticBLS OEWS May 2024 (pay) Official statisticReport
202523,480$109,370BLS OEWS May 2025 Official statisticReport
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