2

Remote Medical Imaging Machine Learning Jobs in Washington

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning ...

Senior Machine Learning Engineer

Arlington, VA · On-site +1

$120K - $165K/yr

Practical knowledge of remote sensing, satellite imagery, or related geospatial domains * Knowledge ... Comprehensive Medical, Dental, and Vision plans * Health Savings Account (HSA) with a company ...

Showing results 21-40

Remote Medical Imaging Machine Learning information

What is a remote medical imaging machine learning specialist?

A remote medical imaging machine learning specialist is a professional who develops and applies machine learning algorithms to analyze medical images, such as X-rays, MRIs, and CT scans, from a remote location. They work with healthcare providers and researchers to improve diagnostic accuracy and streamline image analysis, often using artificial intelligence techniques. This role typically requires expertise in both medical imaging technologies and advanced machine learning, as well as the ability to collaborate virtually with multidisciplinary teams. Their work helps enable faster, more precise medical diagnoses and can contribute to advances in telemedicine.

How does a remote medical imaging machine learning professional typically collaborate with radiologists and other healthcare experts?

Remote Medical Imaging Machine Learning professionals work closely with radiologists, data scientists, and IT teams to develop and refine AI models for diagnostic imaging. Collaboration often occurs through virtual meetings, shared data annotation platforms, and cloud-based model deployments. Regular feedback from radiologists is essential to ensure the models provide clinically relevant and accurate outputs. This teamwork helps bridge the gap between technical development and real-world clinical needs, leading to more effective and reliable imaging solutions.

What are the key skills and qualifications needed to thrive as a remote medical imaging machine learning specialist, and why are they important?

To excel as a Remote Medical Imaging Machine Learning Specialist, you need a solid background in computer science, mathematics, and medical imaging, often supported by a relevant degree (such as in computer science, biomedical engineering, or a related field) and experience with machine learning frameworks. Familiarity with technical tools like Python, TensorFlow, PyTorch, and DICOM imaging systems, along with experience in medical imaging data annotation and model deployment, is typically required. Strong analytical thinking, attention to detail, and effective remote communication skills help differentiate top performers in this field. These competencies ensure the accurate development and deployment of AI models that support clinical decision-making and improve patient outcomes in healthcare environments.

What are the most commonly searched types of Medical Imaging Machine Learning jobs in Washington?

The most popular types of Medical Imaging Machine Learning jobs in Washington are:

What are popular job titles related to Remote Medical Imaging Machine Learning jobs in Washington?

For Remote Medical Imaging Machine Learning jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Remote Medical Imaging Machine Learning jobs in Washington look for?

The top searched job categories for Remote Medical Imaging Machine Learning jobs in Washington are:

What cities in Washington are hiring for Remote Medical Imaging Machine Learning jobs?

Cities in Washington with the most Remote Medical Imaging Machine Learning job openings:

Machine Learning Engineer - Remote

Halvik

Vienna, VA • On-site, Remote

$140K - $150K/yr

Full-time

Re-posted 9 days ago


Job description

Halvik Corp delivers a wide range of services to 13 executive agencies and 15 independent agencies. Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning, Cyber Security and Cutting Edge Technology across the US Government. Be a part of something special!
Role and Responsibilities
Model Development
  • Collaborate with data scientists and SMEs to develop ML models using curated datasets.
  • Conduct experiments, prototypes, and proof-of-concepts to validate model performance.
  • Create scalable and reusable training pipelines using Databricks notebooks and MLflow.

Implementation and Optimisation
  • LLMs (Large Language Models), RAGs, and AI agent systems for various business applications. Deployment & MLOps
  • Operationalize models with robust CI/CD workflows.
  • Deploy models usingMLflow, SageMaker, or custom APIs.
  • Monitor production models for accuracy, drift, and latency; manage retraining schedules.

Data Integration & Architecture Alignment
  • Work closely with Data Engineering to align ML pipelines with the Bronze, Silver, Gold layers of a Medallion Architecture.
  • Engineer high-quality features and maintain training/inference pipelines.

Cloud and Platform Engineering
  • Leverage AWS services including S3, EC2, Lambda, SageMaker, and Step Functions.

Collaboration & Documentation
  • Document ML artifacts, processes, and performance outcomes.
  • Contribute to agile project ceremonies and maintain a feedback loop with stakeholders.
  • Share knowledge and mentor junior team members.

Required Skills:
  • 5+ years of experience in ML Engineering or Applied Machine Learning.
  • Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow).
  • Proficient with Databricks, MLflow, and PySpark.
  • Solid understanding of model lifecycle and MLOps practices.
  • Experience with AWS-based data infrastructure and related DevOps practices.
  • Demonstrated ability to productionize models and integrate with business system
  • Strong understanding of mathematics and statistics relevant to machine learning and AI.
  • Proven experience with machine learning models and algorithms (supervised, unsupervised, deep learning, etc.).
  • Solid background in software engineering principles and best practices.
  • Hands-on experience with model training frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
  • Experience with MLOps tools and workflows, particularly on AWS (SageMaker, Lambda, S3, etc.).
  • Practical experience with LLMs, RAGs, and AI agent architectures.
  • Proficiency with the Databricks platform for data engineering and ML pipelines.
  • Advanced programming skills in Python.
  • Excellent communication and teamwork abilities.

Preferred Skills:
  • Experience building and deploying interactive UIs for AI models using Streamlit, Gradio, or similar frameworks for rapid prototyping and real-time model interactions
  • Business acumen and ability to align AI solutions with organizational goals.
  • Optimize compute and storage resources for performance and cost-efficiency.

Halvik's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Halvik Corp is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.
Halvik's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.