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Machine Learning Biomedical Engineer Jobs in Washington

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join ...

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

Machine Learning Engineer LOCATIONTysons, VA 22182 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

Machine Learning Engineer LOCATIONChantilly, VA 20151 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Machine Learning Engineer LOCATIONReston, VA 20190 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

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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 are popular job titles related to Machine Learning Biomedical Engineer jobs in Washington? For Machine Learning Biomedical Engineer jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Machine Learning Biomedical Engineer jobs in Washington look for? The top searched job categories for Machine Learning Biomedical Engineer jobs in Washington are:
What cities in Washington are hiring for Machine Learning Biomedical Engineer jobs? Cities in Washington with the most Machine Learning Biomedical Engineer job openings:
AI/Machine Learning Engineer

AI/Machine Learning Engineer

Initiate Government Solutions

Washington, DC โ€ข On-site

$129K - $155K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 15 hours ago


Job description

Founded in 2007, Initiate Government Solutions (IGS) is a Woman-Owned Small Business and a fully remote IT services provider supporting federal partners nationwide. We deliver innovative Enterprise IT and Health Services solutions with a strong focus on data analytics, health informatics, cloud migration, AI, and the modernization of federal information systems.
Our vision is to be a health IT trendsetter, continuing to solve the nation's most challenging healthcare IT issues by conceiving, designing, and building solid, creative, and innovative open-source solutions.
Our mission is to innovate, design, and deliver tailored solutions that balance technical advancement with cost-awareness while providing exceptional service.
IGS is currently pipelining for a remote AI/Machine Learning Engineer to support our work within the federal healthcare industry. Candidates will be contacted as opportunities become available for further consideration.
Assignment of Work and Travel:
This is a remote access assignment. The Candidate will work remotely daily and will remotely access VA systems and therein use approved VA provided communications systems. Travel is not required; however, the candidate may be required to attend onsite client meetings as requested.
The AI/Machine Learning Engineer will work alongside a team of highly skilled developers and engineers in the development of AI applications. A motivated and qualified candidate will not only have hands-on development experience in (JavaScript, Python or Java) but also a willingness to collaborate with teams to solve problems. Together we're accelerating our client's digital transformation through the building and deployment of data-driven, scalable AI solutions.
Responsibilities and Duties (Included but not limited to):
  • Design, develop, and deploy machine learning and deep learning models to support clinical decision-making, predictive analytics, and health outcomes research.
  • Fine-tune models for high performance using healthcare-specific data, including EHRs, claims, imaging, and structured/unstructured text.
  • Collaborate with data engineers to clean, preprocess, and normalize healthcare data in compliance with federal data standards (e.g., HL7, FHIR).
  • Build scalable ML pipelines that integrate with federal data platforms and cloud services (e.g., VA's Lighthouse API, Azure Government, AWS GovCloud).
  • Ensure AI/ML solutions meet federal regulations, including HIPAA, FISMA, FedRAMP, and VA Information Security requirements.
  • Implement differential privacy, encryption, and access controls to safeguard sensitive health data.
  • Contribute to the development of governance frameworks to ensure transparent, explainable, and bias-mitigated models.
  • Document model lifecycle, from training to deployment, including risk assessments, validation reports, and audit trails.
  • Work cross-functionally with program managers, clinicians, data scientists, and software developers to identify opportunities for AI/ML applications that improve healthcare delivery and veteran outcomes.
  • Present complex machine learning findings in a way that is actionable and aligned with federal healthcare program goals.
  • Stay updated on the latest developments in AI/ML applications for public health and healthcare operations.
  • Prototype and test emerging AI technologies (e.g., NLP for clinical text, computer vision for imaging diagnostics) for possible integration into government systems.
  • Monitor deployed models for drift, accuracy, and operational effectiveness over time.
  • Maintain model retraining schedules based on new data inputs or policy changes.
  • Prepare comprehensive documentation and reports for internal stakeholders and external oversight (e.g., OMB, GAO, IG audits).
  • Develop dashboards and visualizations to track performance metrics, patient outcomes, and utilization trends impacted by AI/ML tools.

Requirements
  • Bachelor's degree or higher in one of the following disciplines, Computer Science, Data Science, Artificial Intelligence / Machine Learning, Mathematics / Statistics, Biomedical Engineering, Health Informatics, Electrical or Computer Engineering
  • 4+ years of experience in software and machine learning engineering.
  • Strong knowledge of natural language processing (NLP) and transformer models.
  • 5+ years proficiency in Python and hands-on experience with ML libraries like TensorFlow, PyTorch, or Hugging Face Transformers.
  • Proven experience building scalable, cloud-based AI/ML solutions and enhancing custom question answering mapping/workflows.
  • Expertise in the full ML pipeline, including data processing, model training, serving, and monitoring.
  • Knowledge of NLP architectural strategies such as Retrieval-Augmented Generation, Knowledge Graphs, and Agentic Graphs.
  • Expertise in MLOps best practices, including Infrastructure as Code (IaC), CI/CD pipelines tailored for ML workflows, model version control, and real-time performance monitoring to ensure scalable and reliable AI/ML systems.
  • Familiarity with federal AI governance frameworks and compliance standards (e.g., NIST AI RMF, FedRAMP) is a plus.
  • Passion for developing team-oriented solutions to complex engineering problems
  • Excellent communication skills and attention to detail
  • Analytical mind and problem-solving aptitude
  • Ability to obtain and maintain a Public Trust
  • Strong organizational skills

Preferred Qualifications and Core Competencies:
  • Master's degree in one of the above-mentioned fields
  • Preferred Tools & Environments: Python, R, TensorFlow, PyTorch, Scikit-learn, AWS (SageMaker), Azure ML, Databricks, Apache Spark, Power BI, Tableau, Plotly, Git, GitHub/GitLab
  • Active VA Public Trust
  • Prior experience supporting a VA program
  • Prior, successful experience working in a remote environment

Successful IGS employees embody the following Core Values:
  • Integrity, Honesty, and Ethics: We conduct our business with the highest level of ethics. Doing things like being accountable for mistakes, accepting helpful criticism, and following through on commitments to ourselves, each other, and our customers.
  • Empathy, Emotional Intelligence: How we interact with others including peers, colleagues, stakeholders, and customers' matters. We take collective responsibility to create an environment where colleagues and customers feel valued, included, and respected. We work within a diverse, integrated, and collaborative team to drive towards accomplishing the larger mission. We conscientiously and meticulously learn about our customers' and end-users' business drivers and challenges to ensure solutions meet not only technical needs but also support their mission.
  • Strong Work Ethic (Reliability, Dedication, Productivity): We are driven by a strong, self-motivated, and results-driven work ethic. We are reliable, accountable, proactive, and tenacious and will do what it takes to get the job done.
  • Life-Long Learner (Curious, Perspective, Goal Oriented): We challenge ourselves to continually learn and improve ourselves. We strive to be an expert in our field, continuously honing our craft, and finding solutions where others see problems.

Compensation: There are a host of factors that can influence final salary, including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications.
Benefits: Initiate Government Solutions offers competitive compensation and a robust benefits package, including comprehensive medical, dental, and vision care, matching 401K and profit sharing, paid time off, training time for personal development, flexible spending accounts, employer-paid life insurance, employer-paid short and long term disability coverage, an education assistance program with potential merit increases for obtaining a work-related certification, employee recognition, and referral programs, spot bonuses, and other benefits that help provide financial protection for the employee and their family.
Initiate Government Solutions participates in the Electronic Employment Verification Program.