The Biomedical Engineer who writes what everyone assumes
$194,760top of the range in Massachusetts · middle $109,370 / yr
AI augments this role
Biomedical Engineers in the United States earn a median of $109,370 a year. Pay starts near $71,850. Pay reaches $194,760 at the top of the range in Massachusetts, the best-paying state for this work among those with at least 500 people in the job.
Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Bioengineers and Biomedical Engineers, SOC 17-2031). Last checked 9 September 2026.
Entry level
$71,850
Top of the range · Massachusetts
$194,760
Education
Bachelor's in biomedical engineering
Wages — U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Bioengineers and Biomedical Engineers). Top of the range is the highest state-level figure among states with at least 500 people in the job. AI-impact rating is PayCrunch's editorial assessment. Updated September 2026.
🆕 New & Trending AI Tools for Biomedical EngineerReviewed September 2026
We track new AI-tool launches every week and refresh this list — here’s what’s gaining traction for Biomedical Engineer work right now.
AbridgeNEWEnterprise / see site
Ambient AI scribe that turns a patient conversation into structured clinical notes.
How a Biomedical Engineer uses it: document a visit automatically instead of charting after your shift
Microsoft Dragon CopilotNEWEnterprise / see site
Voice AI that dictates and drafts clinical documentation (successor to Nuance DAX).
How a Biomedical Engineer uses it: speak your notes and have the chart written and filed for you
Heidi HealthNEWFree / paid tiers
AI documentation tool built around clinician and nurse workflows.
How a Biomedical Engineer uses it: handle shift notes and handovers without manual write-ups
OpenEvidenceNEWFree for verified clinicians
AI that answers clinical questions from current medical evidence, with citations.
How a Biomedical Engineer uses it: check the latest evidence at the point of care in seconds
NotebookLMNEWFree / $7.99 mo
Google tool that answers questions grounded only in the documents you give it — with citations.
How a Biomedical Engineer uses it: load your own manuals, policies, or PDFs and ask questions that stay accurate to the source
SukiEnterprise / see site
AI voice assistant for clinical notes and coding.
How a Biomedical Engineer uses it: dictate notes hands-free and cut charting time sharply
NablaFree tier / see site
Ambient AI assistant that generates notes from the patient encounter.
How a Biomedical Engineer uses it: capture the visit and get a ready-to-review note in seconds
ChatGPTFree / $20 mo
The most-used AI assistant — writing, analysis, research, and images from a plain-language chat.
How a Biomedical Engineer uses it: draft emails and documents, summarize long files, and get instant answers to on-the-job questions
ClaudeFree / $20 mo
AI assistant known for careful writing, long-document analysis, and coding.
How a Biomedical Engineer uses it: analyze big reports or spreadsheets and turn messy notes into clean, finished writing
The prototype sits in the middle of the table, and the biomedical engineer asks a nurse to try the alarm with one hand, the way a night shift actually works. The circuitry is elegant. The grip fights the user. A clinician cannot spare a second hand when a patient is sliding the wrong way, so the control has to change before anyone talks about a polished housing. Around the table are a mechanical designer, a quality partner, and a regulatory colleague who will ask where this decision lands in the design record. The device has left the classroom. It is something a hospital might trust.
A prototype, a nurse, and the design record
Biomedical engineers design devices, imaging systems, and clinical tools that have to work on real patients and in real departments. One engineer may own a wearable sensor, a pump, an implant component, or the software that sits beside a piece of hardware. Another may work on imaging: the chain from a scanner's signal to a picture a radiologist can read. Another may design clinical systems that move information or alarms through a hospital. The shared craft is design under constraint. Biology, safety, manufacturing, and the way clinicians actually move all get a vote. You do not get to satisfy only the elegant constraint.
The week is requirements, prototypes, tests, and reviews. You write what the device must do, in language a test can check. You build or specify the next version. You watch a bench test, an animal study the company is running, or a simulated clinical use, and you decide whether the failure is a one-off or a design fault. You sit with clinicians who will use the thing, with technicians who will build it, and with quality staff who keep the company's system honest. Tools include CAD, test fixtures, statistical summaries of bench data, risk files, and the design history the company maintains. Places include device manufacturers, imaging companies, hospital clinical-engineering groups that still design, and research labs inside universities that partner with those firms.
Devices sold for medical use in the United States sit under the Food and Drug Administration's oversight. Inside the company, that reality shows up as a quality system you follow: design records, reviews, complaint handling, and the checks the firm uses before a device ships or a change is released. Your job is to work inside that system, not to recite it from memory in an interview. Describe a decision you documented, a test you tied to a requirement, and a complaint or a failure you traced to a cause. Leave clause numbers out of the story. Employers who run a mature quality system can tell whether you have lived in one. They are less impressed by a list of citations than by a change you controlled.
Imaging and clinical-systems work have the same spine with different neighbors. An imaging engineer spends time with physicists, with reconstruction methods, and with the people who will hang a monitor in a dim room. A clinical-systems engineer spends time with nurses, with information-technology staff, and with the alarms and workflows that already fill the unit. Both still document. Both still care when a change could affect a patient. If you want one of those seats, say so. "Medical devices" is a wide phrase. A hiring manager is trying to picture a specific bench.
The Bureau title on the wage chart
The dollars follow Bioengineers and Biomedical Engineers, SOC 17-2031. The Bureau of Labor Statistics released these wages for May 2025 in its Occupational Employment and Wage Statistics program. Bioengineer postings and biomedical engineer postings can share this series, so read the actual duties before you assume the chart matches. A role that is purely sales, or purely hospital equipment repair, belongs to a different conversation and often a different page. No employment count is included, so do not invent a headcount when you talk. Name the Bureau title once, then describe the device, the imaging chain, or the clinical system you would actually design.
An ABET degree, and the public job that may want a PE
The degree companies expect
An ABET-accredited engineering degree is the usual educational door. A Professional Engineer licence is uncommon in this field and still relevant for some public-sector work. Day to day, device companies look at design judgment inside their quality system.
ABET accreditation is how the profession signals that an engineering program met a national review of its curriculum and its outcomes. Employers hiring biomedical engineers look for that mark on a biomedical, bioengineering, electrical, mechanical, or related degree, depending on the bench. A bachelor's is the common door into a design seat. A master's helps when the work is specialized, research-heavy, or aimed at a scientist-engineer hybrid role. A doctorate appears more often in research groups and in university paths than in ordinary product design. Preparation is the accredited degree, lab and design projects, and internships or co-ops where you saw a requirement become a test. A portfolio of projects, with your personal contribution circled in honest language, beats a transcript full of course names and no artifact.
A Professional Engineer licence, granted by a state engineering board, is uncommon for engineers inside a device company. It becomes relevant for some public work: roles where drawings are sealed, where you offer engineering services directly to the public, or where a government employer expects the licence for the post. If that is the chair you want, look at the state board's path and at the experience it requires, and do not treat the licence as a substitute for design skill. If you want product development, imaging, or a hospital innovation group, lead with the ABET degree, the projects, and evidence you can work inside a quality system. Mention the PE only when the posting, or the public nature of the work, makes it part of the job.
What you should be ready to show is a design you influenced. Walk through the user, the requirement, the test, and a change you made when the test failed. If the product was regulated, describe how you followed the company's quality system: who reviewed the change, what record you updated, how a complaint would find its way back to the design. Skip statute trivia. A quality lead listening to you is checking for habits. Those habits are also how you become promotable, because senior engineers are the ones other people trust with the record, not only with the prototype.
How a device company reads a new engineer
Manufacturers, imaging firms, and some large hospital systems hire. Apply to the domain your projects already touch: mechanical design of a device, electronics, software that is part of a medical product, imaging, or quality engineering if that is the seat. Say which. A letter that lists every biomedical topic from anatomy to machine learning tells the reader you have not chosen a bench. Include one project in enough detail that a stranger can see your decisions. If an internship was mostly observation, say what you were allowed to own, even if it was a fixture or a test plan. Inflated ownership is easy to spot in a design review.
Ask who signs the design and how a change gets approved. An engineer who will sit beside a strong senior and a functioning quality system will learn the craft. An engineer hired to "wear all the hats" in a startup with no records may learn speed and may also learn habits a later employer has to undo. Both environments exist. Choose with your eyes open, and describe the environment honestly when you negotiate, because scope is part of pay. Ask whether the role is design, sustaining an existing product, verification, or quality. Sustaining work is real engineering. It should not be advertised as green-field invention if the week is complaints and small changes.
References should include someone who reviewed your design work: a professor on a capstone, an internship mentor, a senior engineer. Ask them to speak about a decision, not only your attitude. In the interview, expect a walk-through. Draw the system, name the risk you worried about, and say what you would measure. When a clinical detail is outside your knowledge, say so and say how you would find it from a user. Biomedical engineering fails when engineers guess about clinicians. It also fails when engineers hide inside process and never decide. Show both the record and the judgment.
Engineer, senior, then design lead or quality
The path runs from engineer to senior engineer, and then toward a design lead or a quality role. An engineer takes a scoped problem, tests it, and documents it under someone else's system ownership. A senior engineer sets approach, reviews other people's designs, and is trusted with harder tradeoffs. A design lead owns a product area or a subsystem and coordinates the people and the record around it. A quality role, for engineers who move that way, owns the system that keeps design, complaints, and release decisions coherent. Some people move into regulatory work beside quality. The fork is real. Both forks still depend on having done the engineering, not only on having attended the meetings.
You are promoted when your designs survive review and your records survive an audit of the company's own system. Keep a private list of products or subsystems, your piece of them, the test that mattered, and the user you designed for. Strip anything confidential before you put it on a resume. That list is how you ask to move from engineer to senior, and how you choose between design leadership and quality leadership later. If the list is only tasks assigned, you are still building the first rung. A PE, if you pursue one for public work, sits beside this ladder for those specific chairs. It does not replace the senior engineer's portfolio inside a device firm. ABET opened the door. Finished, documented design moves you through it.
Massachusetts at the high end, Arizona as typical pay
Entry pay on the chart is $71,850. The national median is $109,370. The gap between them is $37,520. Massachusetts is where the top figure lives, $194,760, and only where the Bureau could release a number for this occupation. The climb from the country's middle to that Massachusetts top is $85,390. Arizona's median, which is typical pay in Arizona, is $141,230. Arizona's median stands $31,860 above the national median. California's median is $128,310. Minnesota's median is $127,730. Massachusetts also has a median, $127,570, and that typical-pay figure is separate from the $194,760 high end in the same state. Pennsylvania's median is $122,560. Talk about $141,230 when you mean what is typical in Arizona. Talk about $194,760 when Massachusetts' top figure is the subject. Talking about Massachusetts requires you to pick which of its two numbers you mean.
A new graduate in a defined engineer seat should compare an offer with $71,850. The $37,520 toward $109,370 is the discussion when you already own a subsystem, run your own reviews, and the offer still reads like a first job. A senior engineer can anchor on $109,370, then on a state median if the work is in Arizona, California, Minnesota, Massachusetts, or Pennsylvania. The Arizona conversation about typical pay uses the $31,860 above the national median, landing on $141,230. A Massachusetts conversation about typical pay uses $127,570, not the high end. The $85,390 from the national median to $194,760 belongs with design-lead scope, a scarce specialty, or a senior quality role with real system ownership, and it is tied to the high end in Massachusetts. It is a weak opening for a first design job anywhere, including in that state.
Keep the script tied to the rung and the place. For an engineer, set the letter beside $71,850 and ask what would justify crossing $37,520: independent design, mentorship of newer hires, or ownership of a record the quality system depends on. For a senior engineer, start at $109,370 and cite a state median only as typical pay. For a design lead or a quality lead discussing the Massachusetts high end, use the $85,390 gap and ask the employer to describe scope in product language, not in adjectives. There is no employment total on this page to wave around. The wage facts you can stand on are entry, the national median, the Massachusetts high end, five state medians plus the three gaps already worked out on the chart. Arizona's typical pay and Massachusetts' high end can both be true. They serve different purposes only if you keep the words "typical" and "high end" attached to the right dollar.
After you agree, the prototype and the record are still the job. An ABET degree is the door. A PE matters in the uncommon public case and can stay off the table for ordinary device work. Follow the company's quality system when the device is regulated, and describe that habit without a string of clause numbers. Engineer, senior engineer, then design lead or quality: that is the climb. Put $71,850 beside a new design seat, $109,370 beside senior work, Arizona's $141,230 beside typical pay in that state, and Massachusetts' $194,760 only beside the high end of the range.
The top of Biomedical Engineer pay — and how to get there with AI
$194,760what Biomedical Engineer pay reaches in Massachusetts
Highest state-level top-of-range annual wage for Bioengineers and Biomedical Engineers, among states with at least 500 people in the job. U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025.
And the role it leads to — Biochemists and Biophysicists — reaches $222,850 in Texas.
$71,850entry$109,370middle$194,760top end
Mid-range biomedical engineers know how the device behaves; the ones paid at the top of the range have written the protocol, the test report and the submission that let the company prove it to somebody outside the building.
Most device teams run on shared memory. Everyone knows which fixture the bench test needs and which material failed last time, and none of it exists in a form a regulator, an auditor or a new hire could follow. The tasks that pay in this job are the written ones: protocols and standards for the use, maintenance and repair of medical equipment, technical reports and data summary documents for regulatory submissions or patent applications, and project plans carrying timelines and capital spending requests. A model turns your bench notes and ANSYS simulation software output into a first draft in an afternoon, which removes the excuse engineers use for putting the writing off, but only somebody who ran the pilot experiment knows which claim the data will not support.
Your playbook, by where you are now
Just startingWrite one protocol properly
Take a bench test you already run and write the protocol for it, complete enough that another engineer gets the same numbers without asking you.
Keep the experiment database yourself: sample, fixture, settings, result, and what went wrong, one row per run.
Draft your test summaries with Claude from your own raw notes, then check every figure against the run record before it leaves your desk.
Find out what the design file for your product is actually missing, and fill one gap in it.
Read the trade literature on the materials your device uses for an hour a week, and write a short internal note whenever something changes a specification.
What proves it: A protocol and a populated experiment database the next engineer on the product uses instead of asking around.
Realistic span: the first two years
A few years inCarry a submission end to end
Own the technical report for one design change, from bench data through to the safety and effectiveness argument.
Build the Dassault Systemes SolidWorks model and the simulation run into the same evidence package, so prediction and physical test answer the same question.
Write the project plan for one equipment improvement, with the timeline and the capital spending request attached.
Sit in on the materials review for an implanted component and take the minutes nobody wants to take.
Ask Perplexity what has been published on a material you are evaluating, then read the papers yourself before repeating any of it internally.
What proves it: A regulatory submission or patent application with your name on the technical sections.
Realistic span: years three through six
ExperiencedSet the standard the group works to
Write the maintenance and repair standard every device in your line is held to, and get it formally adopted.
Run the schedules, inventory and contract deadlines for a team of engineers so the documentation load is planned rather than panicked.
Turn the experiment databases into the argument behind the next capital request.
Train incoming engineers on the protocol format so the habit outlives you.
What proves it: A company standard in force and a team working to schedules you set.
Realistic span: year seven and after
The next 90 days
Pick the bench or pilot experiment you have repeated most in the past year and spend ninety days turning it into a document. Write what the experiment is for, the instrumentation and process formula it assumes, the fixture setup, the acceptance criteria, and the three ways it has gone wrong. Then hand it to an engineer who has never run it and watch where they stall. Those stalls are the parts you have been carrying in your head. Fix them, put the finished protocol into the design file, and mention it the next time somebody is deciding equipment specifications. Writing the thing everyone assumes is the cheapest way to become the person consulted about it.
Wage figures: BLS OEWS, May 2025. The playbook is PayCrunch editorial guidance, not a guarantee of pay or placement.
Every figure is the national median from the U.S. Bureau of Labor Statistics (OEWS) shown on that role’s own page.
Never used AI before? Start here (2 minutes).
Start by speeding your simulation and analysis work. Use ChatGPT or Claude to write and debug the Python/MATLAB that processes your bench-test or biosignal data, and to plan a simulation study before you run it in your FEA/CFD tool. Getting to validated results faster is the core engineering skill that moves you from support work into device R&D, where the pay is.
For the regulated side, use general AI to learn and draft — explain a section of ISO 14971 or the 510(k) pathway, then draft against it — and dedicated medtech tools like Greenlight Guru for the actual quality system. Keep patient data and proprietary IP out of consumer tools, and have a qualified engineer review every regulated document.
The one rule, forever: Medical devices are regulated and life-critical: AI-drafted regulatory documents, verification, and code must be reviewed and owned by a qualified engineer — never let AI replace design controls, ISO 14971 risk management, or clinical validation. Never paste confidential IP, patient data, or unpublished trial data into a consumer AI tool. Patient safety and FDA compliance are your responsibility, not the model's.
The plays — exact steps, exact prompts
Do these in order. Each one is copy-paste ready. You do not need to know anything about AI going in.
1
Simulate faster with AI-accelerated FEA/CFD
Why this pays: R&D salaries reward engineers who get a validated design to test quickly. AI-accelerated simulation and surrogate models let you sweep far more design variants and cut physical prototypes, compressing development cycles — the productivity that gets devices shipped and earns senior R&D pay.
Use Ansys SimAI or COMSOL to run your structural/fluid/thermal simulations, and let AI surrogate models predict performance across a design space before you commit to full runs.
2
Have AI design the simulation study and sanity-check your interpretation of the results.
Copy-paste this prompt
I'm simulating a [device, e.g. a cardiovascular stent / an orthopedic implant / a microfluidic channel] for [objective, e.g. fatigue life / flow shear stress]. Help me design the study: the load cases and boundary conditions, the mesh and convergence approach, the material models to consider, and how to validate the simulation against physical test data. Then list the failure modes I must check and the assumptions most likely to invalidate the result.
Simulation guides design; physical verification and validation confirm it. Never rely on FEA/CFD alone for a patient-contacting device — you own the V&V.
What you'll haveMore design iterations and fewer prototypes — the development speed that ships devices and earns senior R&D roles.
2
Draft regulatory and quality documents faster
Why this pays: Regulatory submissions and design-control documentation are the chronic bottleneck between a finished device and revenue. The engineer who drafts a clean 510(k), design history file, or risk analysis quickly — with human review — is invaluable to any medtech and commands a premium.
Greenlight GuruChatGPTClaude
1
Manage design controls and risk in Greenlight Guru, and use ChatGPT or Claude to draft narrative sections and trace matrices from your inputs — then route everything through your regulatory/quality reviewer.
2
Turn your technical inputs into a structured regulatory draft.
Copy-paste this prompt
Help me draft a substantial-equivalence rationale for a 510(k) for [device type] versus predicate [device class/description]. Structure it with intended use, technological characteristics, a comparison table, and how any differences don't raise new questions of safety or effectiveness. Use only the general, non-confidential details I provide, and flag every place I must add verified data or a citation. This is a draft for expert review, not a submission.
A regulatory professional reviews and owns every submission. Never paste confidential predicate data, trade secrets, or clinical data into a consumer tool.
What you'll haveFaster, cleaner regulatory and design-control drafts — the submission speed that unblocks revenue and makes you indispensable.
3
Build ML into devices and diagnostics
Why this pays: AI/ML medical devices — imaging triage, wearables, biosignal diagnostics — are the highest-paid, fastest-growing corner of biomedical engineering. The engineer who can develop and validate a model that clears regulatory scrutiny sits at the top of the pay band.
Python (PyTorch/TensorFlow)MATLAB (AI features)Hugging Face
1
Prototype and train models in Python (PyTorch/TensorFlow) or MATLAB, using ChatGPT/Copilot to scaffold the pipeline, and design the validation to a clinical, not just statistical, standard.
2
Scaffold a rigorous ML pipeline with a validation plan fit for a regulated device.
Copy-paste this prompt
Scaffold an ML pipeline in [PyTorch] to classify [biosignal/image, e.g. ECG arrhythmia / retinal images] from [public dataset]. Include data splits that prevent leakage, preprocessing, a baseline and a stronger model, the clinically meaningful metrics (sensitivity/specificity, not just accuracy), calibration, and an external validation plan. Note the bias, generalizability, and 'AI as a medical device' regulatory considerations I must document.
Use only public or properly de-identified, consented data. Model performance must be clinically validated and documented — patient-facing claims require regulatory rigor.
What you'll haveValidated ML models built to a clinical bar — the AI-medical-device skill set that sits at the top of biomedical pay.
4
Accelerate literature and predicate research
Why this pays: Fast, deep research de-risks projects and sharpens design reviews — the engineer who knows the mechanisms, failure modes, and predicate landscape leads projects instead of following them. That leadership visibility is what earns promotions and pay.
ElicitConsensusPubMed
1
Use Elicit or Consensus to synthesize the literature on a device mechanism or clinical need and to surface failure modes, then confirm the key claims in the primary papers on PubMed.
2
Build a fast, cited evidence and predicate-device summary for a design review.
Copy-paste this prompt
Summarize the current evidence on [device mechanism or clinical problem, e.g. drug-eluting stent restenosis / continuous glucose sensor drift]: the leading design approaches, the documented failure modes and complications, and the key studies with their findings. Then list comparable cleared/approved predicate devices and how they differ. Provide citations I can verify, and flag where the evidence is weak or conflicting.
AI can misattribute or hallucinate citations — verify every source in the primary literature before you rely on it in a design decision.
What you'll haveDeeper, faster, cited research — the command of evidence and predicates that makes you the engineer who leads projects.
5
Automate test analysis and V&V protocols
Why this pays: Rigorous, fast verification and validation is what actually gets a product to market. Using AI to write the analysis code and draft protocols turns V&V from a slog into throughput — the reliability that ships products and marks you for advancement.
Python (with ChatGPT)MATLABJMP / Minitab
1
Have ChatGPT or Claude write Python/MATLAB to analyze your bench-test data and use JMP/Minitab for the statistics, then draft V&V protocols the team can execute.
2
Generate a defensible test protocol and analysis plan for a design verification.
Copy-paste this prompt
Draft a design-verification test protocol for [device requirement, e.g. tensile strength of a suture anchor / accuracy of a pulse-oximeter reading]. Include the acceptance criteria tied to the requirement, sample size with a statistical rationale, the test method and equipment, the data-analysis plan, and how results feed the design history file. Note the standards that likely apply and where I must confirm them.
You own the acceptance criteria, sample-size justification, and standards applicability — verify each. AI drafts the protocol; a qualified engineer approves it.
What you'll haveFaster, statistically sound V&V and analysis — the rigor that gets products to market and gets you promoted.
Your 12-month sequence to the top of the range
How the plays above stack into a path from median pay toward the $194,760 tier.
Month 1
Use AI to write the code that analyzes your test/biosignal data and to plan one simulation study. Validate results physically.
Months 2-3
Draft a regulatory or design-control document with AI (human-reviewed) and speed literature/predicate research with Elicit/Consensus.
Months 3-6
Prototype an ML model on public data with a clinical-grade validation plan, and standardize AI-drafted V&V protocols.
Months 6-12
Deepen either AI/ML device development or regulatory expertise — the two niches that reach the $194,760 tier.
Gear for this job
As an Amazon Associate, PayCrunch earns from qualifying purchases. Links to books and tools are for the job on this page; we only recommend what we’d use in the work.
Same live O’Reilly 3rd already on data-scientist / python-developer / market-research-analyst / biomedical-researcher. This leftover page opens with write and debug the Python/MATLAB that processes your bench-test or biosignal data; play 5 is Automate test analysis and V&V protocols with Python/MATLAB. Not CompTIA Data+ and not leftover Ross Exam P (that is actuary). Confirm 109810403X. Live page HTTP 200, no PC_GEAR / amazon.com/dp / tag=paycrunch-20 at 2026-09-17 4:44 PM PT.
Next steps for a Biomedical Engineer
Some links below are affiliate or partner links. PayCrunch may earn a commission if you enroll or subscribe through them, at no extra cost to you. Wage figures on this page still come from the Bureau of Labor Statistics, not from these programs.
Biomedical Engineer work is specific enough that a stamped 'check out these courses' block would be noise. BLS files this work as Bioengineers and Biomedical Engineers (SOC 17-2031). O*NET Job Zone 4 is typical: a bachelor's degree, so the honest next credential is a professional certificate or bachelor's-level coursework — not a random catalog dump.
The occupation's listed knowledge areas include Engineering and Technology and Physics; the links search those subjects, not a generic 'career courses' list.
Biomedical Engineers in this dataset list Autodesk AutoCAD among the tools in use, so a program that names that stack is a better fit than a survey course.
Coursera search for engineering and technology — a professional certificate or bachelor's-level coursework that lines up with engineering, not a generic professional-development aisle.
FlexJobs screens remote, hybrid, freelance, and flexible listings so you are not wading through unverified ads. This is a job-board search for Biomedical Engineer work, not a claim that they list a counted SOC 17-2031 inventory.
Write a Biomedical Engineer resume, or one aimed at Biochemists and Biophysicists, instead of a blank template. Resume Now is a resume builder; we are not claiming a counted template set for this SOC.
A Biomedical Engineer resume that names the actual tasks on this page, or the step-up title Biochemists and Biophysicists, beats a blank template when you apply.
What Biomedical Engineers earn by state
These are the Bureau of Labor Statistics’ own figures for Bioengineers and Biomedical Engineers, state by state — not a cost-of-living adjustment applied to the national number. Only states employing at least 500 people in the occupation are shown, because a state median drawn from a handful of workers is noise rather than a signal.
Arizona
$141,230
highest of them · +29% vs the national median
Texas
$92,600
lowest of the 13 states that qualify · -15% vs the national median
The same job pays $48,630 more a year at the median in Arizona than in Texas — 53% higher. That gap is what the Bureau measured, before any question of what it costs to live in either place. The top-of-range figure quoted at the head of this page, $194,760, is a different statistic in a different place: it is the 90th-percentile wage in Massachusetts. The state that pays the typical worker most and the state where the best-paid go highest are not always the same one.
Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025, SOC 17-2031. 13 states clear the 500-employee reporting floor for this occupation; those below it are left out rather than shown with a wide error band.
Free data. Use any of it.
PayCrunch publishes verified, BLS-sourced salary + AI-playbook data on 1,000+ professions — free, no signup.
No. AI can simulate, draft, and model, but it cannot own design controls, sign off risk analysis, run clinical validation, or take responsibility for patient safety and FDA compliance — all of which are legally and ethically human. AI is becoming a core tool of the trade; the biomedical engineers who master it, especially those who build AI into devices, are the ones commanding the top salaries.
Can I trust AI-generated regulatory documents or simulations?
Only as drafts and predictions you verify. An AI-written 510(k) section or risk file must be reviewed by a qualified regulatory/quality professional; an AI-accelerated simulation must be validated against physical test data. AI can hallucinate a citation or misapply a boundary condition with total confidence. In a regulated, life-critical field, the human review and the responsibility are non-negotiable.
Is it safe to use ChatGPT with device or patient data?
Not with confidential IP, patient data, or unpublished clinical or predicate data — keep those out of consumer tools entirely. Use general AI for learning, generic-parameter analysis, and drafting, and use validated, access-controlled enterprise or medtech-specific systems (like Greenlight Guru) for anything sensitive or regulated. When training models, use only public or properly de-identified, consented data.
How does AI actually increase a biomedical engineer's pay?
By moving you toward the highest-value work and doing it faster. AI-accelerated simulation and V&V ship devices sooner; AI-drafted regulatory work clears the bottleneck to revenue; and building and validating ML into devices puts you in the best-paid niche in the field. Development speed plus AI-device expertise is what moves you from median toward the $194,760 tier.
Which AI skill should a biomedical engineer prioritize?
AI-assisted coding for simulation, data analysis, and — if you can — machine learning, because it compounds across every project and opens the highest-paid AI-medical-device roles. Pair it with a general assistant (ChatGPT/Claude) for regulatory drafting and research. Start by automating the data analysis you already do by hand each week.
Methodology & sources
Salary (median, 10th, top of the range) — U.S. Bureau of Labor Statistics, OEWS.
By state — the Bureau of Labor Statistics’ own state medians, limited to states employing at least 500 people in the occupation. No cost-of-living arithmetic is applied to a wage anywhere on this page.
The plays — PayCrunch's own step-by-step guidance using publicly available AI tools. Tool names/URLs are real and current as of August 2026; prompts written to work as-is. Verify any professional output before relying on it.