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Medical Machine Learning Jobs in Washington (NOW HIRING)

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Medical Machine Learning information

See Washington salary details

$41.3K

$186.6K

$381.7K

How much do medical machine learning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for medical machine learning in Washington is $186,574.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,500.00 and $304,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Medical Machine Learning position, and why are they important?

To thrive in Medical Machine Learning, you need a strong background in computer science, statistics, and biomedical sciences, often supported by an advanced degree in a related field. Familiarity with programming languages (such as Python or R), machine learning frameworks (like TensorFlow or PyTorch), and healthcare data management systems is crucial. Strong problem-solving abilities, collaboration skills, and the ability to communicate complex technical concepts to a diverse audience make a candidate stand out. These skills are critical for developing robust, effective machine learning solutions that can impact patient care and integrate seamlessly into clinical workflows.

What is a Medical Machine Learning job?

A Medical Machine Learning job involves developing and applying AI algorithms to analyze medical data, such as imaging, electronic health records, and genomics, to improve diagnosis, treatment, and patient outcomes. Professionals in this field work with clinicians, data scientists, and engineers to create predictive models, automate medical workflows, and ensure compliance with healthcare regulations. Strong knowledge of machine learning, data processing, and healthcare-specific challenges is essential.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often found in tech companies or healthcare organizations. These roles usually require advanced skills in machine learning, deep learning, and data analysis, along with extensive experience and sometimes specialized certifications. Compensation at this level reflects leadership responsibilities, expertise, and the impact of AI solutions in the organization.

Is ML a high paying job?

Medical machine learning professionals typically earn high salaries due to the specialized skills required, such as expertise in data analysis, programming, and healthcare knowledge. Salaries can vary based on experience, education, location, and industry demand, but overall, it is considered a well-compensated field within tech and healthcare sectors.

Will MLE be replaced by AI?

Medical Machine Learning Engineers (MLEs) develop and implement algorithms to analyze medical data, and AI advancements are augmenting their work rather than replacing it. While AI tools automate certain tasks, MLEs are essential for designing, validating, and maintaining complex models within healthcare environments, often requiring domain expertise and programming skills. The role is expected to evolve with AI, emphasizing collaboration between human expertise and automated systems.

What does machine learning do in healthcare?

In healthcare, machine learning is used by professionals to analyze large datasets, improve diagnostic accuracy, and develop predictive models for patient outcomes. Medical machine learning specialists often work with algorithms, programming tools, and clinical data to enhance treatment plans and healthcare efficiency.

What types of teams do Medical Machine Learning professionals typically collaborate with in a healthcare setting?

Medical Machine Learning professionals often work in multidisciplinary teams that include data scientists, clinicians, software engineers, and regulatory experts. Collaboration with healthcare providers is common to ensure models address real clinical needs and comply with healthcare standards. You'll typically interact closely with IT departments for data access and security, as well as with research teams and sometimes external partners. Working in such dynamic teams allows you to contribute technical expertise while gaining insights from domain experts, leading to more successful and impactful machine learning projects.

What are popular job titles related to Medical Machine Learning jobs in Washington? For Medical Machine Learning jobs in Washington, the most frequently searched job titles are:
What cities in Washington are hiring for Medical Machine Learning jobs? Cities in Washington with the most Medical Machine Learning job openings:
Research Associate, Atmospheric Science, Machine Learning

Research Associate, Atmospheric Science, Machine Learning

DeVine Consulting, Inc.

Silver Spring, MD โ€ข On-site

$90K - $110K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago


Job description

DeVine provides technical and scientific support to government clients in Oceanography & Atmospheric Science among other technical disciplines.
Our company is looking for a Research Associate, with experience in Atmospheric Science and Machine Learning (ML), to join DeVine in a full time capacity. This position will be supporting a government customer, hence only US Citizens may be considered for hire. Candidates who meet/exceed every requirement may be considered for remote work.
DeVine contributes to projects in data modeling, remote sensing & machine learning. We collaborate with our clients in scientific analysis of the Earth's atmosphere & ocean and land surfaces, as well as astronomy and astrometry. We help our clients test and operate space-based, air-based, subsurface, and land and ocean surface-based sensors.
The successful hire will contribute to improvements in weather forecast performance to deliver more accurate weather insights to our customers.
If your experience is relevant to the requirements below, and you'd enjoy working in Silver Spring, MD, then please apply!
Duties:
  • Conduct innovative research at the intersection of weather prediction and machine learning, including approaches that leverage observations from satellite constellation
  • Develop, verify, and document forecast improvements that provide measurable value to customers
  • Partner with engineering and product teams to transition research advances into scalable, operational systems
  • Communicate results through internal reviews, customer discussions, and, where appropriate, conferences or publications
  • Contribute broadly to improving forecasts and overall product performance

Required experience and credentials:
  • Graduate degree in atmospheric science, meteorology, computer science, or a related field
  • 2+ years of experience developing ML models for weather applications
  • Strong ML engineering fundamentals, including model training, validation, evaluation, and documentation
  • Training, running, and verifying AI-based weather prediction models
  • Working in cloud-based computing environments
  • Handling large meteorological datasets and common data formats at scale
  • Modern deep learning frameworks (e.g., PyTorch or TensorFlow)
  • Large geophysical dataset formats (GRIB, NetCDF, ZARR)
  • Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow)
  • Familiarity with cloud-based computing environments (AWS, GCP, Azure)
  • Strong written and verbal communication skills
  • Ability to manage multiple projects and balance competing priorities
About the position:
  • Position Type: Full-time, Must be U.S. Citizen
  • Location: Silver Spring, MD
  • Benefits: Medical, Dental, Vision, 401K, Life Insurance, Paid Holidays, Paid Sick Leave and Paid Vacation
  • Compensation: $90K to $110K per year salary range DOE and skills

Equal Opportunity Employer
We are committed to a policy of assuring that all applicants for employment are recruited, hired and assigned on the basis of qualifications and merit without discrimination based on any protected classification, including, but not limited to, race, color, religion, sex, sexual orientation, national origin, veteran status, age, disability, handicap, marital status, or any other characteristic protected by applicable laws.