Machine Learning Engineer

Hybrid | Washington D.C. | 3-4 Days a Week Onsite

Active TS/SCI Clearance Required

Summary

Our client is an employee and Service-Disabled, Veteran-owned Small Business focused on providing niche technical services. They are a team of experienced cybersecurity professionals with a track record of success in the Federal, Commercial, and Academic workspaces. Additionally, our client designs, builds, operates, and secures scalable cloud and IT infrastructures to meet their customers’ near-term needs and fulfill their long-term requirements.

Responsibilities

Our client is looking for a Machine Learning Engineer to join their team! As a Machine Learning Engineer with cloud experience, you will be responsible for developing and deploying machine learning models to solve complex problems across a cloud infrastructure that houses sensitive data and models that support mission critical operations. You will work closely and collaborate with a dynamic cross-functional team crafting data pipelines for model training to implement machine learning algorithms.

• Develop and deploy machine learning models to solve complex problems related to various mission focus areas
• Leverage various cloud platforms such as AWS, Azure, or Google cloud to build, train, and deploy machine learning models at scale
• Collaborate with team members to establish data pipelines for model training and inference
• Implement and optimize machine learning algorithms for efficiency and performance
  
• Conduct thorough experimentation and analysis to improve model accuracy and performance
  
• Participate in informal and formal code reviews
• Participate in architectural reviews and offer alternative architectural patterns to optimize application performance 
• Document processes and solutions that serve as communication findings for both technical and non-technical stakeholder

Requirements

• 8+ years of experience in computer science, data science, machine learning
• Proven experience developing and deploying machine learning models in a production environment
• Hands-on experience with major cloud platforms 
• Strong proficiency in programming languages such as Python, along with libraries like Tensorflow, PyTorch, or scikit-learn
• Understanding of version control, testing, and debugging
• Strong communications skills with the ability to effectively convey technical concepts to various stakeholders and audiences
• Agile development experience along with related technologies (e.g., Jira)  
• Experience within the following is required:
  
  • GitLab
  • Python and R Studio
  • Cloud Services (AWS, GCP, Oracle)
  • Natural Language Processing (NLP)
  • Data Science
  • Machine Learning

Preferred Requirements

• Deep knowledge of security best practices, experience with cloud security tools, and working with role and attribute based security models 
• Deep knowledge of DevSecOps and MLOPs
• Familiarity and experience with the Intelligence Community (IC), and the intel cycle
• Familiarity and experience with the Department of Homeland Security (DHS)
• A Master’s degree or equivalent experience in a related field is preferred

Education/Certification Requirements

• A Bachelor’s degree or equivalent practical experience is required

Clearance Requirements

• Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; an active TS/SCI clearance is required. Please be aware that onboarding can take 4-6 weeks for this position.