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Machine Learning Biomedical Engineer Jobs in Pennsylvania

JOB SUMMARY We are seeking a hands-on Machine Learning Engineer to design, build, evaluate, deploy, and maintain machine learning models in production environments. The ideal candidate will have ...

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you'll have the opportunity to be part of a leading ML innovation organization that develops a wide range of ...

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you'll have the opportunity to be part of a leading ML innovation organization that develops a wide range of ...

Senior Machine Learning Engineer

Malvern, PA Β· On-site

$120K - $158K/yr

We are assisting our client in hiring for a Senior Machine Learning Engineer. Our client is an established SaaS company serving banks, credit unions, and fintechs. Their cloud-based platform helps ...

Machine Learning Engineer III

Pittsburgh, PA Β· On-site

$111K - $133K/yr

They are seeking a Senior Machine Learning Engineer to develop and optimize machine learning models aimed at enhancing patient care and operational efficiency in hospital settings. Responsibilities ...

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Machine Learning Biomedical Engineer information

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.

What are popular job titles related to Machine Learning Biomedical Engineer jobs in Pennsylvania?

For Machine Learning Biomedical Engineer jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Machine Learning Biomedical Engineer jobs in Pennsylvania look for?

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

What cities in Pennsylvania are hiring for Machine Learning Biomedical Engineer jobs?

Cities in Pennsylvania with the most Machine Learning Biomedical Engineer job openings:

Infographic showing various Machine Learning Biomedical Engineer job openings in Pennsylvania as of September 2026, with employment types broken down into 8% Internship, 72% Full Time, and 20% Part Time. Highlights an 90% In-person, and 10% Hybrid job distribution.

Machine Learning Engineer

Philadelphia, PA β€’ On-site

Compunnel
IT ServicesΒ β€’Β 501 - 1,000 employees

Contractor

Re-posted 13 days ago


Job description

JOB SUMMARY
We are seeking a hands-on Machine Learning Engineer to design, build, evaluate, deploy, and maintain machine learning models in production environments. The ideal candidate will have strong expertise in Python, PySpark, AWS, and machine learning model development, with a proven track record of delivering production-ready models that drive business outcomes. This role requires a highly technical individual contributor who can analyze data, compare model performance, optimize solutions, and manage the complete machine learning lifecycle. Experience with local LLM deployments is required, but the primary focus of this role is traditional machine learning model development and production deployment.
KEY RESPONSIBILITIES
β€’ Design, develop, train, test, and deploy machine learning models for enterprise-scale business applications.
β€’ Analyze new and existing datasets to evaluate opportunities for model improvements and enhanced predictive performance.
β€’ Build, compare, and validate multiple machine learning models to determine the most effective production solution.
β€’ Perform feature engineering, model selection, hyperparameter tuning, and model optimization.
β€’ Develop scalable data processing pipelines using Python and PySpark.
β€’ Deploy, monitor, maintain, and improve machine learning models in production environments.
β€’ Assess model performance using appropriate statistical methods and machine learning evaluation metrics.
β€’ Collaborate with business stakeholders and technical teams to identify opportunities for machine learning solutions.
β€’ Conduct exploratory data analysis and provide insights to support data-driven decision-making.
β€’ Work with large-scale datasets within AWS cloud environments.
β€’ Develop reproducible machine learning workflows and maintain technical documentation.
β€’ Troubleshoot production model issues and implement continuous improvements.
β€’ Support experimentation and proof-of-concept initiatives related to machine learning and AI technologies.
β€’ Configure and manage local LLM environments where required to support business use cases.
β€’ Participate in technical discussions, code reviews, and best practice initiatives.
REQUIRED QUALIFICATIONS
β€’ Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field.
β€’ Minimum 5 years of experience as a Machine Learning Engineer.
β€’ Strong hands-on programming expertise in Python.
β€’ Recent and relevant experience using PySpark for large-scale data processing and machine learning workflows.
β€’ Proven experience developing, training, evaluating, and deploying machine learning models into production environments.
β€’ Experience comparing multiple machine learning algorithms to determine the best-performing production solution.
β€’ Strong understanding of machine learning concepts, including:
- Classification
- Regression
- Clustering
- Ensemble Methods
- Random Forest
- Gradient Boosting
- Feature Engineering
- Model Evaluation
β€’ Experience working with AWS cloud services and machine learning infrastructure.
β€’ Strong data analysis and statistical modeling skills.
β€’ Experience monitoring, maintaining, and improving production machine learning models.
β€’ Experience working with large and complex datasets.
β€’ Knowledge of machine learning lifecycle management and model governance.
β€’ Experience setting up and managing local Large Language Models (LLMs).
β€’ Strong debugging, analytical, and problem-solving skills.
β€’ Ability to independently manage projects and deliver technical solutions.
β€’ Excellent communication and collaboration skills.
PREFERRED QUALIFICATIONS
β€’ Experience with MLOps tools and model monitoring frameworks.
β€’ Experience with machine learning experimentation platforms.
β€’ Familiarity with distributed computing and big data technologies.
β€’ Experience optimizing machine learning workloads in cloud environments.
β€’ Knowledge of advanced machine learning algorithms and predictive analytics techniques.
β€’ Experience within telecommunications, construction workflow management, or enterprise operations environments.
β€’ Exposure to Generative AI technologies in addition to traditional machine learning solutions.
CERTIFICATIONS
β€’ AWS Certified Machine Learning - Specialty (Preferred)
β€’ AWS Certified Solutions Architect - Associate or Professional (Preferred)
β€’ Databricks Machine Learning Certification (Preferred)
β€’ Google Professional Machine Learning Engineer (Preferred)
β€’ Relevant Python, Data Science, or Machine Learning Certifications (Preferred)

Compunnel logo

About Compunnel

Sourced by ZipRecruiter

Compunnel is a well-known company located in Plainsboro, NJ, US, recognized in the industry of IT Services and Solutions. Established in 1989, Compunnel offers a suite of services that help businesses integrate technology efficiently into their operations, a recognizable name in the IT solutions sphere for over three decades. The company’s service portfolio includes Digital Transformation, Business Intelligence, Cloud Services, Cybersecurity, and Application Modern Services, among others. Guided by its mission "to innovate with industry-leading digital solutions and disruptive tech strategies for unimagining business growth," the company underlines its commitment to offering out-of-the-box solutions to its clients. Remarkable achievements of the company include serving more than 30 Fortune 500 companies and providing job opportunities for over 50,000 individuals.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

1994

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