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Internship Machine Learning Compiler Engineer Jobs in Maryland

Geico

Machine Learning Engineer II

Bethesda, MD · Hybrid

$105K - $215K/yr

Leverage expertise in machine learning, software engineering, and system architecture to independently drive the development of production-ready models. Work closely with cross-functional teams, from ...

Autodesk

Senior Machine Learning Engineer

California, MD · On-site +1

$100K - $137K/yr

Position Overview As a Senior Machine Learning Engineer, you will play a key role in designing, developing, and evolving machine learning systems that support conversational AI, search, multi-agent ...

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Internship Machine Learning Compiler Engineer information

What is the difference between Internship Machine Learning Compiler Engineer vs Internship Software Engineer?

AspectInternship Machine Learning Compiler EngineerInternship Software Engineer
FocusDeveloping and optimizing compilers for machine learning modelsDesigning, coding, and testing software applications across various domains
SkillsMachine learning, compiler design, programming (C++, Python)Programming, algorithms, software development
Work EnvironmentResearch labs, tech companies, AI-focused teamsTech companies, startups, software firms
Industry UsageAI, machine learning, deep learning industriesBroad software development across industries

Internship Machine Learning Compiler Engineers focus on creating and optimizing compilers for machine learning models, requiring knowledge of AI and compiler design. In contrast, Internship Software Engineers work on developing general software applications across various fields. Both roles involve programming skills but differ in their specialization and industry focus.

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Machine Learning Engineer

Machine Learning Engineer

Maverc Technologies

Columbia, MD

Full-time

Re-posted 24 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.


Apply