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Entry Level Medical Imaging Machine Learning Jobs

nudge

Machine Learning Engineer

San Francisco, CA · On-site

About the role As a Machine Learning Lead at Nudge, you will drive the development of next ... Lead the design and development of imaging algorithms that leverage in-house ultrasound transducers ...

Aston Carter

Machine Learning Engineer

Manhattan, NY · Remote

$125/hr

REMOTE Machine Learning Engineer This project-based consulting role invites an experienced Machine ... Medical, dental & vision * Critical Illness, Accident, and Hospital * 401(k) Retirement Plan - Pre ...

New

Nudge

Machine Learning Engineer

San Francisco, CA · On-site

About the role As a Machine Learning Lead at Nudge, you will drive the development of next ... Lead the design and development of imaging algorithms that leverage in-house ultrasound transducers ...

QT Imaging, Inc.

$120 - $180/hr

Experience working with DICOM imaging data. * Knowledge of machine learning and artificial ... Experience supporting FDA-regulated medical device development is preferred. * Experience ...

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Entry Level Medical Imaging Machine Learning information

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How much do entry level medical imaging machine learning jobs pay per hour?

As of Aug 28, 2026, the average hourly pay for entry level medical imaging machine learning in the United States is $17.46, according to ZipRecruiter salary data. Most workers in this role earn between $15.62 and $18.99 per hour, depending on experience, location, and employer.

What is the difference between Entry Level Medical Imaging Machine Learning vs Entry Level Medical Imaging Technologist?

AspectEntry Level Medical Imaging Machine LearningEntry Level Medical Imaging Technologist
Required CredentialsBasic understanding of machine learning, programming skills, relevant certifications in AI or data scienceCertification in radiologic technology, ARRT certification, associate degree in radiologic technology
Work EnvironmentResearch labs, healthcare tech companies, hospitals focusing on AI integrationHospitals, clinics, imaging centers performing diagnostic scans
Employer & Industry UsageTech companies, healthcare startups, research institutionsHospitals, diagnostic imaging centers, outpatient clinics

Entry Level Medical Imaging Machine Learning roles focus on developing and applying AI algorithms to improve imaging diagnostics, requiring programming and data analysis skills. In contrast, Entry Level Medical Imaging Technologists operate imaging equipment directly to produce diagnostic images, requiring radiologic technology certifications. Both roles are essential in healthcare but differ significantly in skills, environment, and responsibilities.

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Entry Level Medical Imaging Machine Learning jobs near you
Infographic showing various Entry Level Medical Imaging Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 15% Part Time, and 7% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $36,327 per year, or $17.5 per hour.

Machine Learning Engineer

Oakbrook Terrace, IL • On-site

Darwill, Inc.
Marketing • 201 - 500 employees
Learn more about Darwill, Inc.external

Full-time

Posted 3 days ago

New

Job description

Overview
Darwill is a nationally recognized print and marketing communications firm based in the west suburbs of Chicago. As a premier provider of complex, data-driven marketing solutions, we help CMOs and marketing leaders drive measurable performance through advanced analytics, automation, and AI-powered insights.
We are seeking a Machine Learning Engineer (MLOps) to support the productionization of traditional machine learning models (e.g., propensity and segmentation models) while also building and maintaining the core data pipelines on Databricks that power our analytics and modeling platforms.
This role is intentionally scoped for a mid-level engineer: someone with enough experience to work independently and make sound engineering decisions, but who is still hands-on, execution-focused, and eager to grow. This is not an entry-level position, and it is not a principal or architect-level role.
Location
Chicago, IL area (Oak Brook / West Suburbs)
Hybrid work model with 1-2 days onsite per week required
Reports To
VP of Data Engineering & Data Science
Responsibilities / Essential Functions
Data Engineering & Platform Foundations
  • Design, build, and maintain ETL pipelines in Databricks using Spark and Delta Lake
  • Independently implement data transformations, joins, and aggregations across large, multi-source datasets
  • Build and maintain data validation and quality checks to ensure reliability of downstream analytics and ML workflows
  • Optimize Databricks jobs for performance, scalability, and cost efficiency
  • Write and maintain clear technical documentation for data pipelines and tables

ML Engineering & MLOps
  • Partner closely with Data Scientists to support traditional ML model development, including feature engineering, training, validation, and deployment
  • Productionize propensity, ranking, and segmentation models used in large-scale marketing campaigns
  • Build and maintain repeatable ML pipelines for training, batch scoring, and inference
  • Implement model versioning, experiment tracking, and reproducibility standards
  • Support model performance monitoring, drift detection, and retraining cycles

Deployment, Monitoring & Operations
  • Deploy data pipelines and ML workflows into production environments serving millions of records
  • Implement monitoring and alerting for data and ML pipelines
  • Support A/B testing and model performance evaluation in partnership with Data Science
  • Troubleshoot production issues independently and collaborate effectively when escalation is needed

GenAI (Secondary / Directional)
  • Contribute to GenAI initiatives as capacity allows
  • Stay informed on emerging AI technologies and tooling
  • (GenAI is not the primary focus of this role today.)

Required Qualifications
Experience
  • 3-6 years of professional experience in machine learning engineering, data engineering, or a closely related role
  • Experience working in production environments with minimal day-to-day supervision
  • Demonstrated ability to collaborate effectively with Data Scientists and translate models into production systems

Technical Skills (Must-Have)
Data Engineering & Platform
  • Apache Spark (PySpark, SparkSQL)
  • Databricks (ETL pipelines, workflows, Delta Lake)
  • Strong SQL skills (complex queries, joins, window functions, optimization)
  • Experience building and maintaining scalable data pipelines

Programming & Machine Learning
  • Python (pandas, numpy, scikit-learn; experience with XGBoost or LightGBM preferred)
  • Feature engineering and data preparation for ML models
  • Working knowledge of supervised learning models (classification, regression, ranking)

MLOps & Production
  • Experience deploying ML models into production
  • Model versioning and experiment tracking (e.g., MLflow or similar)
  • Monitoring data quality and model performance in production
  • Supporting retraining and validation workflows

Cloud & Tooling
  • Experience with a major cloud platform (Databrick, AWS)
  • Familiarity with workflow orchestration tools (Databricks Workflows or similar)

Preferred Qualifications (Nice-to-Have)
  • Experience with propensity modeling, customer segmentation, or marketing analytics
  • Exposure to CI/CD concepts for data and ML pipelines
  • Experience with Docker or containerized deployments
  • Exposure to GenAI, LLMs, or RAG-based systems
  • Master's degree in Computer Science, Statistics, or a related field
  • Seniority Level
    Associate
  • Industry
    • Marketing Services
  • Employment Type
    Full-time
  • Job Functions

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