Cloud Machine Learning Operations Specialist

7 hours ago

Wilmington, North Carolina, United States STRATUS Solutions Full time
About Us

At Stratus Solutions, we're innovating to solve real-world problems. Our team of experts enhances the ability of federal government customers to preserve national security, deliver justice, and serve the public with advanced technologies and quality analysis.

We work closely with agencies and industry to overcome technical and cultural hurdles to innovation, empowering them with the latest end-to-end cloud infrastructure, big data, and cyber capabilities.

Our expertise in cross-domain and boundary solutions, network analytics, DevOps, and low-to-high development is unique in our industry. We develop and deliver innovative products and applications that are deployed in highly sensitive customer environments and have broad applications for federal missions.

As a member of our team, you'll be working to solve real-world problems on missions that matter with people who share your passions and encourage your ambition.

We're committed to hiring great people who are passionate about their work and want to make a difference. We empower them with the autonomy, support, and tools they need to fulfill their true potential.

Job Summary

We're seeking a highly skilled Cloud Machine Learning Operations Specialist to join our team. The ideal candidate will have a strong background in machine learning operations, experience with NVIDIA Triton, and a passion for working with cloud-based technologies.

As a Cloud Machine Learning Operations Specialist, you'll be responsible for designing and managing scalable and high-performance inference pipelines in a production, enterprise system. You'll collaborate with data scientists and software engineers to deploy machine learning models, ensuring optimal performance, resource utilization, and cost tracking and savings.

You'll also be responsible for architecting and implementing solutions to scale machine learning inference to handle large workloads efficiently. Additionally, you'll monitor and fine-tune model inference for optimal speed and resource utilization, implement automation tools and processes for model deployment, monitoring, and scaling, and develop robust monitoring and logging solutions to track model performance, system health, and data quality in real-time.

As a member of our team, you'll have the opportunity to work on exciting projects, collaborate with a cross-functional Product team, and contribute to the development of innovative products and applications.

Responsibilities
  • Design and manage scalable and high-performance inference pipelines in a production, enterprise system
  • Collaborate with data scientists and software engineers to deploy machine learning models, ensuring optimal performance, resource utilization, and cost tracking and savings
  • Architect and implement solutions to scale machine learning inference to handle large workloads efficiently
  • 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, system health, and data quality in real-time
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
  • Experience with other MLOps tools and platforms
  • 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 the ability to work effectively in a collaborative team environment
  • Excellent communication skills and the ability to convey technical concepts to both technical and non-technical stakeholders
Preferred Qualifications
  • 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
What We Offer
  • Excellent compensation and amazing benefits
  • Multiple health insurance options
  • 401k Immediate Vesting. Company matches 100% of the first 3% contributed and 50% of the next 2% contributed.
  • 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 where employees don't have to use leave for up to 3 days out of the year for inclement weather or budget issues.
  • Employee-centric culture and a belief that we should empower those who are good at what they do and then give them the tools they need to achieve success and grow their career.
  • A commitment to learning and growth and easy ways to achieve both including a training budget, education assistance, mentorship programs, and collaborative learning sessions.
  • A collaborative environment that fosters communication and an open-door policy.

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