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Machine Learning Biomedical Engineer Jobs in Pennsylvania

PYTHON, ANALYSIS RoleMachine Learning Engineer Industry TypeIT Services & Consulting Functional AreaData Science & Analytics Employment TypeFull Time, Permanent Role CategoryData Science & Machine ...

AI / Machine Learning Engineer Proven experience in data science, including data analysis, model development, and machine learning algorithms. Strong proficiency in Python for developing back-end ...

As a machine learning engineer in the AI for Autonomy Lab, you willidentify, shape, apply, conduct, and lead engineering research that matches critical U.S. government needs. The AI for Autonomy Lab ...

As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for the machine learning systems that power our data discovery and model improvement ...

As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for the machine learning systems that power our data discovery and model improvement ...

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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.
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 June 2026, with employment types broken down into 77% Full Time, 22% Part Time, and 1% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution.
Machine Learning Engineer[C2C/W2 ROLE]

Machine Learning Engineer[C2C/W2 ROLE]

SmartIPlace

Philadelphia, PA โ€ข On-site

Contractor

Posted 18 days ago


Job description

Job Title: Machine Learning Engineer [w2 role]

Location:ย Philadelphia, PA (Onsite โ€“ 4 days/week at 1800 Arch Street)
Alternate location:ย Reston, VA (for strong candidates)
Duration:ย Contract
Eligibility:ย USC, GC


Job Summary

We are seeking aย hands-on Machine Learning Engineerย with 5+ years of experience who can design, build, and deploy scalable machine learning solutions. This role requires strong coding expertise and real-world experience delivering models into production environments. The ideal candidate is not a manager but an individual contributor who thrives in a fast-paced, engineering-focused environment.


Key Responsibilities

  • Model Development:ย Design, build, train, and fine-tune machine learning and deep learning models for real-world use cases
  • Production Deployment:ย Deploy, monitor, and maintain ML models in production environments
  • Data Pipeline Development:ย Build and optimize scalable data pipelines for ingestion, transformation, and processing
  • Performance Optimization:ย Evaluate models using metrics like accuracy, recall, and AUC; optimize for performance and scalability
  • Collaboration:ย Work closely with cross-functional teams including data engineers, software engineers, and business stakeholders

Required Skills & Qualifications

  • 5+ years of experience as a Machine Learning Engineer or similar role
  • Strongย Python programmingย skills with solid software engineering fundamentals
  • Recent and hands-on experience with PySparkย (mandatory)
  • Experience with machine learning frameworks such asย Scikit-learn
  • Strong understanding ofย statistics, probability, and algorithms
  • Experience working withย SQL, data modeling, and large datasets
  • Proven track record ofย deploying ML models into production environments
  • Experience withย AWS services

Preferred Qualifications

  • Experience withย MLOps toolsย such as Docker for model deployment
  • Hands-on experience withย local Large Language Models (LLMs)
  • Familiarity with distributed computing and big data technologies

Interview Process

Round 1 (30 mins โ€“ Virtual)

  • Experience overview
  • Technical discussion
  • Live coding exerciseย (Video ON + full desktop screen sharing required)

Round 2 (60 mins โ€“ In-Person Preferred)

  • Technical deep dive
  • Advanced live coding exercise

Work Environment

  • 4 days onsite preferred (Philadelphia office)
  • Open to relocation candidates
  • Reston, VA location may be considered if needed

Smart-iPlace logo

About Smart-iPlace

Sourced by ZipRecruiter

SMART-iPLACE provides innovative staffing and consulting solutions that help our clients achieve their business objectives. We can understand and support all areas of your IT systems from back-end infrastructure to front-end personal productivity. Our goal is create innovative IT solutions that enable your business to be more agile and competitive.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Irving, TX, US

Year founded

2021

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