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Machine Learning Biomedical Engineer Jobs (NOW HIRING)

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Machine Learning Engineer

Fort Mill, SC ยท Remote

$48/hr

Job Title Machine Learning Engineer Location Remote Rate $48/hr on W2 Must Haves: Neaural networks NLP Python AZURE Pytorch or tensorflow Machine Learning Engineer / AI Engineer Role Role Overview ...

FloVision Solutions

Machine Learning Engineer

POSITION OVERVIEW As a Machine Learning Engineer at FloVision, you will design, develop, and optimize computer vision models and deep learning capabilities across our product portfolio. Rather than ...

Orchard LLC

Machine Learning Engineer

Machine Learning Engineer Remote with occasional travel to Silver Spring, MD About @Orchard: @Orchard is a growing Woman-Owned Small Business and federal prime contractor delivering mission-critical ...

Venturegloballng

Engineer, Machine Learning

Arlington, VA ยท On-site

$157K - $185K/yr

Engineer, Machine Learning Located: Arlington Summary The Machine Learning Engineer will design, develop, and maintain the productionization of machine learning, deep learning, generative AI, large ...

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Machine Learning Biomedical Engineer information

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$31.5K

$128.8K

$193.5K

How much do machine learning biomedical engineer jobs pay per year?

As of Sep 2, 2026, the average yearly pay for machine learning biomedical engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

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.

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.

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.

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.

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Cities with the most Machine Learning Biomedical Engineer job openings:

What states have the most Machine Learning Biomedical Engineer jobs?

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The top searched job categories for Machine Learning Biomedical Engineer jobs are:

Machine Learning Biomedical Engineer jobs near you
Infographic showing various Machine Learning Biomedical Engineer job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

Cymertek Corporation

Honolulu, HI โ€ข On-site

Full-time

Re-posted 28 days ago

Job description

Job Summary:
Cymertek Corporation is seeking a talented and innovative Machine Learning Engineer to join their team and help build intelligent systems that drive impactful business solutions. In this role, you will design, develop, and deploy machine learning models to solve complex problems and improve decision-making processes while collaborating with data scientists, engineers, and product teams.
Responsibilities:
โ€ข Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
โ€ข Ability to design, implement, and optimize machine learning models and workflows
โ€ข Experience working with large, complex datasets
โ€ข Knowledge of data preprocessing and feature engineering
โ€ข Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
โ€ข Strong problem-solving skills and analytical thinking
Qualifications:
Required:
โ€ข TS/SCI Full Poly (Please note this position requires full U.S. Citizenship)
โ€ข Bachelor's Degree
โ€ข Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
โ€ข Ability to design, implement, and optimize machine learning models and workflows
โ€ข Experience working with large, complex datasets
โ€ข Knowledge of data preprocessing and feature engineering
โ€ข Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
โ€ข Strong problem-solving skills and analytical thinking
โ€ข Proficiency in programming languages (e.g., Python, R, Java)
โ€ข Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
โ€ข Expertise in model evaluation techniques and metrics
โ€ข Strong knowledge of version control tools (e.g., Git)
โ€ข Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau)
โ€ข Understanding of database technologies (e.g., SQL, NoSQL)
Preferred:
โ€ข Experience with natural language processing (NLP)
โ€ข Knowledge of deep learning techniques (e.g., CNNs, RNNs)
โ€ข Familiarity with deployment tools (e.g., Docker, Kubernetes)
โ€ข Experience with data augmentation and synthetic data generation
โ€ข Ability to collaborate in cross-functional teams (e.g., engineers, product managers)
โ€ข Knowledge of edge computing and model optimization for deployment
Company:
With headquarters in Maryland, Cymertek [/'sฤซ-mer-tek/] Corporation provides superior consulting services for the implementation of high quality information systems. Founded in 2010, the company is headquartered in Laurel, USA, with a team of 11-50 employees. The company is currently Early Stage.

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