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Executive Full Stack Machine Learning Engineer Jobs in Maryland

Responsibilities: • Build a full stack application in collaboration with machine learning and artificial intelligence engineers doing novel computer vision model development. • Interact with ML ...

Overview Python Full Stack Developer Onsite | Ft. Meade | Onsite (may be flexibility for the right ... Data Visualization, Machine Learning Engineering, LLM Integration * Passion for technology and the ...

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Executive Full Stack Machine Learning Engineer information

What is the difference between Executive Full Stack Machine Learning Engineer vs Data Scientist?

AspectExecutive Full Stack Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, Engineering, or related; often requires experience in ML and full stack developmentBachelor's/Master's in Data Science, Statistics, or related; strong analytical and statistical skills
Work EnvironmentDevelops end-to-end ML solutions, integrates backend and frontend, collaborates with engineering teamsAnalyzes data, builds models, visualizes insights, often in research or analytics teams
Industry UsageUsed in tech companies, startups, and enterprises deploying ML productsCommon in research institutions, analytics firms, and data-driven organizations

The Executive Full Stack Machine Learning Engineer focuses on building and deploying complete ML solutions, combining software engineering and data science skills. In contrast, Data Scientists primarily analyze data and develop models without necessarily handling full stack development. Both roles require strong technical credentials but differ in scope and daily tasks.

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in Maryland? The most popular types of Full Stack Machine Learning Engineer jobs in Maryland are:
What are popular job titles related to Executive Full Stack Machine Learning Engineer jobs in Maryland? For Executive Full Stack Machine Learning Engineer jobs in Maryland, the most frequently searched job titles are:
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Full-time

Re-posted 17 days ago


Job description

Become part of a team solving the most significant Cybersecurity & IT Challenges and helping keep the world’s largest and most elite brands safer from cyber threats. At Maverc we have a powerful mindset based on our core values of being accountable, helpful, adaptable, and focused. Maverc Technologies is a proven and effective small business partner and consultant, recognized as a leader in providing cyber security and IT services to the Federal, State, and local Government and within the Intelligence Community. Maverc Technologies is seeking an Machine Learning Engineer to support one of our corporate customers.



Job Duties and Responsibilities 

A talented Machine Learning Engineer to support our AI Center of Excellence! In this role, you and your team will be responsible for the entire lifecycle of machine learning models, from managing and deploying them to troubleshooting any pipeline issues that arise. We offer a collaborative environment where you will work closely with engineers and data scientists to bring impactful ML solutions to life.

Responsibilities include, but are not limited to:

  • Manage and deploy machine learning models into production
  • Debug and troubleshoot issues with deployment pipelines
  • Utilize and understand core ML tooling
  • Work with dataframes to manipulate and prepare data for models
  • Collaborate with the various teams within the AI Center of Excellence to ensure successful model implementation
  • Analyze large amounts of information to discover trends and patterns
  • Build predictive models and machine-learning algorithms


QUALIFICATIONS AND EXPERIENCE 

  • Active SECRET
  • US Citizenship
  • Minimum of 8 years’ experience in DevOps or MLOps
  • Understanding of machine learning modeling techniques and algorithms
  • Experience with Python, Docker, Kubernetes and Git
  • Skilled in common data science libraries (Scikit-learn, PyTorch, etc)
  • Strong math skills (e.g. statistics, algebra)
  • Problem-solving aptitude
  • Excellent communication and presentation skills
  • Experience with deploying open-source LLMs
  • DataBricks
  • Splunk
  • Continuous Integration/Continuous Deployment
  • Knowledge of statistics and concepts in neural networks


Education: Bachelor’s or Master’s in Computer Science, Computer Engineering, or other related field.