Cloud Machine Learning Operations (MLOps) Engineer

Intelligent Decisions - Fulton, MD

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