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Machine Learning Biomedical Engineer Jobs in Texas

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Machine Learning Biomedical Engineer information

What is the difference between Machine Learning Biomedical Engineer vs Data Scientist in Biomedical Industry?

AspectMachine Learning Biomedical EngineerData Scientist in Biomedical Industry
Required CredentialsDegree in Biomedical Engineering, Computer Science, or related fields; knowledge of machine learning and biomedical dataDegree in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentResearch labs, healthcare institutions, biotech companiesHealthcare analytics firms, research institutions, biotech companies
Employer & Industry UsageDevelops algorithms for medical devices, diagnostics, and treatment planningAnalyzes biomedical data to inform clinical decisions, research, and product development

Both roles require expertise in machine learning and biomedical data, but Machine Learning Biomedical Engineers focus on developing algorithms for medical applications, while Data Scientists analyze biomedical data to support research and clinical decisions.

What does a Machine Learning Biomedical Engineer do?

A Machine Learning Biomedical Engineer applies machine learning techniques to solve problems in biology and medicine. They develop algorithms and models to analyze complex biomedical data, such as medical images, genetic information, or sensor readings. Their work supports advancements in diagnostics, treatment planning, and personalized medicine. Typically, they collaborate with clinicians, researchers, and other engineers to design systems that improve healthcare outcomes.

What are the key skills and qualifications needed to thrive as a Machine Learning Biomedical Engineer, and why are they important?

To thrive as a Machine Learning Biomedical Engineer, you need a strong background in biomedical engineering, data analysis, and machine learning, typically supported by a degree in biomedical engineering, computer science, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks (e.g., TensorFlow, PyTorch), and experience with medical imaging or signal processing tools are commonly required. Critical thinking, problem-solving, and the ability to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These abilities are crucial for developing innovative healthcare solutions, ensuring regulatory compliance, and bridging the gap between technology and medicine.

How does a Machine Learning Biomedical Engineer typically collaborate with clinicians and researchers in a healthcare setting?

Machine Learning Biomedical Engineers often work closely with clinicians and researchers to develop algorithms that solve real-world medical challenges. Collaboration usually involves understanding clinical needs, translating them into technical requirements, and iteratively refining models based on feedback from medical experts. Regular meetings, interdisciplinary project teams, and direct participation in data collection or validation studies are common. This collaborative environment ensures that technical solutions are both innovative and clinically relevant, making communication and adaptability essential skills.
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What job categories do people searching Machine Learning Biomedical Engineer jobs in Texas look for? The top searched job categories for Machine Learning Biomedical Engineer jobs in Texas are:
What cities in Texas are hiring for Machine Learning Biomedical Engineer jobs? Cities in Texas with the most Machine Learning Biomedical Engineer job openings:
Machine Learning Biomedical Engineer jobs near you
Infographic showing various Machine Learning Biomedical Engineer job openings in Texas as of May 2026, with employment types broken down into 97% Full Time, 1% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

LEAD ENGINEER - SR. COMPUTER SCIENTIST - Kinesioception Lead

SWRI

San Antonio, TX • On-site

$92K - $121K/yr

Full-time

Posted 27 days ago

Job description

  • Identify and pursue new research directions for current and emerging technologies in machine learning, data science and analytics, biomedical engineering, neuromorphic processing, and human performance optimization.
  • Guide junior staff and customers in R&D concepts and practices and implementation of decision-support solutions.
  • Provide recommendations to management regarding technical direction.
  • Capture new research projects with new and existing clients.
  • Establish an industry presence by presenting our research and networking at conferences, workshops, and symposiums.

  • Apply state-of-the art machine learning software solutions for various decision-support intelligent system applications.
  • Interact with team members and customers to discuss technical solutions to problems.
  • Manage the various aspects of a project (e.g., technical goals, team tasking, project budget, reporting).
  • Interact with clients (and potential clients) to discuss and propose technical solutions to unique problems.

  • Requires a Bachelors, Masters or a PhD in Computer Science, Biomedical Engineering, Electrical Engineering, or directly related degree field- 3 years experience with PhD, 4 years experience with Masters, 5 years experience with Bachelors.
  • 3-5 years: Industry experience in software development, machine learning, biomedical, medical, or human performance optimization applications. Experience with neural network development and associated tools and frameworks preferred.
  • 1+ years: Business development experience; identifying and sourcing potential leads and customers; engaging with customers and identifying problem to be solved and developing statements of work; contract negotiation and closing the deal.
  • Experience with leading project teams, budgets, schedules, risk management; excellent written, verbal, interpersonal skills.
  • A valid/clear driver's license is required.

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