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Biomedical Data Engineer Jobs in Raleigh, NC (NOW HIRING)

... data pertaining to any special assignments Regulatory Compliance - 25% * Ensure the accuracy and ... Minimum 5 years' experience working with biomedical equipment in a clinical engineering environment

... data pertaining to any special assignments Regulatory Compliance - 25% * Ensure the accuracy and ... Minimum 5 years' experience working with biomedical equipment in a clinical engineering environment

Standardize disease and biomarker data using controlled biomedical vocabularies and classifications ... Partner with engineering teams and participate in the full development lifecycle, from research and ...

Standardize disease and biomarker data using controlled biomedical vocabularies and classifications ... Partner with engineering teams and participate in the full development lifecycle, from research and ...

Sr. R&D Engineer

Morrisville, NC ยท On-site

$97K - $134K/yr

Perform statistical analysis and interpret data to guide technical decisions and product ... S. in Mechanical Engineering, Biomedical Engineering, or a related field with 8+ years of ...

Principal Electrical Engineer

Morrisville, NC ยท On-site

$130K - $159K/yr

The ideal candidate brings deep expertise in biomedical sensing hardware, a track record of ... noise data acquisition systems. * Experience designing low-power architectures and battery ...

Senior Electrical Engineer

Morrisville, NC ยท On-site

$100K - $131K/yr

S. in Electrical or Biomedical Engineering or a related field. Preferred Qualifications ... data streaming. * Experience directing and reviewing work from external PCB layout and design ...

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Biomedical Data Engineer information

See Raleigh, NC salary details

$15

$61

$85

How much do biomedical data engineer jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for biomedical data engineer in Raleigh, NC is $61.22, according to ZipRecruiter salary data. Most workers in this role earn between $52.12 and $68.94 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a biomedical data engineer, and why are they important?

To thrive as a Biomedical Data Engineer, you need strong programming skills (e.g., Python, R), a background in biomedical sciences or bioinformatics, and experience with data modeling and analysis. Familiarity with big data frameworks, cloud platforms, and tools like SQL, Hadoop, and machine learning libraries, as well as relevant certifications, is commonly required. Excellent problem-solving abilities, attention to detail, and effective collaboration with cross-functional teams help you stand out in this role. These skills enable accurate analysis and integration of complex biomedical data, supporting critical healthcare research and innovation.

What are some common challenges faced by biomedical data engineers when integrating clinical data from multiple sources?

Biomedical Data Engineers often encounter challenges related to data heterogeneity when integrating clinical information from diverse sources such as electronic health records, medical imaging systems, and genomic databases. These sources may use different formats, standards, and terminologies, making data cleaning and normalization a complex task. Additionally, ensuring patient privacy and compliance with healthcare regulations adds another layer of complexity. Collaborating with clinicians, data scientists, and IT teams is essential to address these challenges and ensure data is usable for research and decision-making.

What is a biomedical data engineer?

A Biomedical Data Engineer is a professional who designs, develops, and maintains systems for collecting, storing, and analyzing biomedical data. They work at the intersection of healthcare and technology, collaborating with researchers, clinicians, and IT specialists to ensure that medical data is accessible, accurate, and secure. Their work supports medical research, diagnostics, and the development of healthcare solutions by leveraging large datasets, machine learning, and advanced analytics. Biomedical Data Engineers often use programming languages, database management, and data processing tools to handle complex health data from various sources.

What is the difference between Biomedical Data Engineer vs Biomedical Data Analyst?

AspectBiomedical Data EngineerBiomedical Data Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Computer Science, or related fields; experience with data engineering toolsBachelor's or Master's in Biology, Bioinformatics, or related fields; proficiency in data analysis and visualization
Work EnvironmentDevelops data pipelines, manages databases, and ensures data infrastructure for research and healthcareAnalyzes datasets, creates reports, and interprets data for research or clinical decision-making
Employer & Industry UsageResearch institutions, biotech companies, healthcare providersHospitals, research labs, biotech firms, healthcare organizations

While both roles work with biomedical data, Biomedical Data Engineers focus on building and maintaining data infrastructure, whereas Biomedical Data Analysts interpret and analyze data to support research and clinical decisions.

What are popular job titles related to Biomedical Data Engineer jobs in Raleigh, NC?

For Biomedical Data Engineer jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Biomedical Data Engineer jobs in Raleigh, NC look for?

The top searched job categories for Biomedical Data Engineer jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Biomedical Data Engineer jobs?

Cities near Raleigh, NC with the most Biomedical Data Engineer job openings:

Infographic showing various Biomedical Data Engineer job openings in Raleigh, NC as of June 2026, with employment types broken down into 84% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $127,343 per year, or $61.2 per hour.

Lead AI Engineer, Biomedical & Vigilance Innovation Software

Front Door Defense

Durham, NC โ€ข On-site

$120 - $160/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 10 days ago


Job description

Lead AI Engineer, Biomedical & Vigilance Innovation Own and drive the development of production-grade AI platforms for pharmacovigilance and safety signal detection

Location: North Carolina, United States

About The Role

United Therapeutics is a biopharma company focusing on rare and cuttingโ€‘edge therapies.

We are seeking a Lead AI Engineer with a startโ€‘up mindset to design, develop, and deploy advanced AI solutions that transform how biomedical insights are generated and how safety signals are detected, assessed, and acted upon. The role operates at the intersection of data science, software engineering, and medical safety, applying advanced analytics, machine learning, and automation to create scalable platforms that support proactive risk management and accelerate informed decisionโ€‘making across the product lifecycle.

Key Responsibilities
  • Design, build, validate, and maintain machine learning, natural language processing, and generative AI solutions for biomedical and pharmacovigilance use cases.
  • Develop tools that support adverse event intake, case triage, coding assistance, duplicate detection, signal prioritization, and trend analysis.
  • Engineer predictive models to identify emerging risks, patient patterns, and operational bottlenecks.
  • Translate complex scientific and business requirements into productionโ€‘ready AI applications.
  • Own model definition, fineโ€‘tuning, and optimization to ensure fitโ€‘forโ€‘purpose AI solutions for the UT patient safety business.
  • Define and execute a bold technology strategy spanning global patient safety, embedding AI, machine learning, and agentic automation across dayโ€‘toโ€‘day PV operations, analytics, and signal detection.
  • Drive the architecture, development, and delivery of nextโ€‘generation platforms for pharmacovigilance AI initiatives.
  • Integrate structured and unstructured data from safety databases, clinical systems, literature, realโ€‘world evidence, and external repositories.
  • Create staging schemas and mine diverse sources for hidden trends and meaningful insights.
  • Build scalable pipelines for data ingestion, transformation, and quality control.
  • Apply ontology mapping, terminology harmonization, and metadata strategies across MedDRA, WHO Drug, and related standards.
  • Ensure robust data lineage, traceability, and audit readiness.
  • Support modernization of pharmacovigilance and organovigilance systems through AIโ€‘enabled automation and decision support tools.
  • Improve case processing efficiency, medical review, and governance reporting via AIโ€‘enabled solutions.
  • Contribute to nextโ€‘generation surveillance models for novel modalities such as xenotransplantation, cell therapy, gene therapy, and organโ€‘based therapeutics.
  • Develop AIโ€‘enabled dashboards and visualization tools for rapid interpretation of safety trends.
  • Ensure AI models and digital tools align with GxP, privacy, security, validation, and regulatory expectations.
  • Support model governance including performance monitoring, unbiased detection, explainability (XAI), and change control.
  • Maintain documentation for validation, testing, intended use, and lifecycle management.
  • Collaborate with safety, clinical, regulatory, medical affairs, biostatistics, and IT teams.
  • Provide technical guidance to analysts, data scientists, and business partners.
  • Deliver validated AI solutions that create measurable gains in vigilance quality, speed, and insight generation.
  • Improve detection and prioritization of safety signals through advanced analytics.
  • Enhance case processing and review efficiency while preserving quality and compliance.
  • Establish reliable, scalable biomedical data assets for future innovation.
  • Maintain regulatoryโ€‘ready governance for AIโ€‘enabled safety systems.
  • Advance our leadership position in responsible AI for the future of medicine.
  • Perform other duties as required.
Minimum Requirements
  • Bachelorโ€™s, Masterโ€™s, or PhD in computer science, engineering, applied mathematics, data science, biomedical engineering, bioinformatics, artificial intelligence, or related field, with the following experience: 8+ years with a Bachelorโ€™s, 6+ years with a Masterโ€™s, or 2+ years postโ€‘PhD.
  • 5+ years of experience in AI engineering, machine learning, or advanced analytics within biopharma, healthcare, or regulated industries.
  • 5+ years of handsโ€‘on expertise in AI tools such as Python, R, MATLAB, TensorFlow, PyTorch, and cloudโ€‘based ML platforms.
  • Track record of deploying AI, machine learning, and data science solutions that deliver measurable outcomes in production environments.
  • Entrepreneurial, transformationโ€‘oriented mindset able to move from concept to execution quickly and lead technologyโ€‘driven change.
  • Background in AIโ€‘native product development, including agentic AI, LLMโ€‘powered applications, autonomous systems, computer vision, or MLโ€‘driven process optimization.
  • Strong problemโ€‘solving capability and ability to operate in complex matrixed environments.
  • Deep fluency in cloudโ€‘native engineering, platform architecture, and modern software development practices.
  • Experience with external innovation strategies, academic partnerships, and emerging technology investments.
  • Engineering mindset to build productionโ€‘grade, compliant, and scalable platforms, not just proofโ€‘ofโ€‘concept demos.
  • Excellent communication skills for conveying technical outputs to nonโ€‘technical stakeholders and senior leadership.
  • Ability to learn scientific domains quickly and ask insightful questions to drive technology improvements in manufacturing timelines, quality, and cost.
Preferred Qualifications
  • 5+ years of experience with NLP, LLMs, knowledge graphs, or biomedical text mining.
  • Experience with safety systems such as Argus, ArisG, Veeva, or equivalent platforms.
  • Knowledge of pharmacovigilance, clinical development, biomedical data, or healthcare regulations.
  • Exposure to drugs, biologics, devices in the rare disease space or advanced therapeutics.
  • Curiosity about and willingness to develop deep domain expertise in pharma automation workflows, advanced analytics, and riskโ€‘identification methodologies.
  • Handsโ€‘on experience with pharmacokinetic (PK) / pharmacodynamic (PD) modeling and simulation applied to AI in pharmacovigilance.
  • Familiarity with GVP, FDA, EMA, ICH, and data privacy frameworks.
Benefits

This position will be located at our Durham, NC office with a hybrid schedule of 4 days in office and the option to work 1 day each week from home. Eligible employees may participate in the Companyโ€™s comprehensive benefits suite, including medical, dental, vision, prescription coverage, employee wellness resources, savings plans (401k, ESPP), paid time off, paid parental leave, disability benefits, and more.

Equal Opportunity Employer

United Therapeutics Corporation is an Equal Opportunity Employer, including veterans and individuals with disabilities. We strive to engage the minds, hearts, and most spirited efforts of each employee. This is a stimulating place to work.

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