Intelligent Decisions - Fulton, MD

posted about 1 month ago

Full-time
Fulton, MD
Computer and Electronic Product Manufacturing

About the position

The Cloud Machine Learning Operations (MLOps) Engineer at Applied Insight plays a crucial role in enhancing the capabilities of federal government customers by leveraging advanced technologies and cloud infrastructure. This position focuses on building enterprise-scale environments using AWS technologies and DevOps methodologies, while collaborating with cross-functional teams to deploy machine learning models and optimize performance. The role involves working on dynamic professional services engagements, ensuring security, automation, and effective monitoring of machine learning operations.

Responsibilities

  • Enhance workflows and processes by building an enterprise-scale environment using AWS technologies and DevOps methodologies.
  • Collaborate with data scientists and software engineers to deploy machine learning models, ensuring optimal performance and resource utilization.
  • Architect and implement solutions to scale machine learning inference for large workloads.
  • Monitor and fine-tune model inference for optimal speed and resource utilization.
  • Implement automation tools and processes for model deployment, monitoring, and scaling.
  • Develop robust monitoring and logging solutions to track model performance and system health in real-time.
  • Help implement security best practices to protect machine learning models and data.
  • Maintain detailed documentation of machine learning operations processes and best practices.
  • Provide technical support for debugging and resolving issues related to model deployment and inference.

Requirements

  • TS/SCI W/ POLY clearance required.
  • Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
  • Proven experience (3+ years) as a Machine Learning Operations Engineer with a focus on NVIDIA Triton.
  • Strong programming skills in Python.
  • Familiarity with machine learning frameworks like TensorFlow or PyTorch.
  • Experience with GPU hardware and optimization for deep learning workloads.
  • Strong problem-solving skills and ability to work effectively in a collaborative team environment.
  • Excellent communication skills to convey technical concepts to both technical and non-technical stakeholders.
  • Solutions Architect Associate credential or other Associate (In Progress acceptable).

Nice-to-haves

  • Proficiency in containerization technologies and orchestration tools (e.g., Docker, AWS Fargate, Amazon Elastic Container Service, AWS Elastic Kubernetes Service).
  • Knowledge of DevOps practices and continuous integration/continuous deployment (CI/CD) pipelines.
  • Familiarity with the AWS cloud platform.
  • Previous experience in the deployment of machine learning models in production environments.

Benefits

  • Multiple health insurance options
  • 401k Immediate Vesting with company matching
  • Fully paid long-term disability, short-term disability, and life insurance
  • Flexible Spending Account options
  • Generous paid time off
  • Flexible work schedules with the ability to bank extra hours for additional time off
  • Government shutdown protection
  • Employee centric culture
  • Commitment to learning and growth with training budget and education assistance
  • Collaborative environment fostering communication and open-door policy
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