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MLOps Engineer (Washington)

MLOps Engineer (Washington)

Progeny Systems CorporationWashington, DC, US
9 hours ago
Job type
  • Part-time
Job description

Job Title

General Dynamics Mission Systems (GDMS) engineers a diverse portfolio of high technology solutions, products and services that enable customers to successfully execute missions across all domains of operation. With a global team of 12,000+ top professionals, we partner with the best in industry to expand the bounds of innovation in the defense and scientific arenas. Given the nature of our work and who we are, we value trust, honesty, alignment and transparency. We offer highly competitive benefits and pride ourselves in being a great place to work with a shared sense of purpose. You will also enjoy a flexible work environment where contributions are recognized and rewarded. If who we are and what we do resonates with you, we invite you to join our high-performance team!

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

Basic Qualifications

Education Requirements :

Bachelor's of Science in a STEM (Science, Technology, Engineering, Mathematics) related field, plus 8 yrs or Master's degree plus 6 yrs.

Due to the nature of work performed within our facilities, U.S. citizenship is required.

Responsibilities for this Position

Key Responsibilities :

  • Model Deployment : Deploy machine learning solutions into production in diverse environments, ensuring they operate correctly and efficiently.
  • Automation : Use tools to automate ML workflows and setting up CI / CD pipelines, including data preprocessing, model training, and model serving.
  • Monitoring : Continuously monitor the performance of machine learning models to detect and fix issues quickly.
  • Collaboration : Work with data scientists and software engineers to integrate ML models into applications and services.
  • Optimization : Optimize models and systems for better performance and scalability.

Skills You'll Bring :

  • Expertise in the full life cycle of ML operations, or previously in an ML Ops role.
  • Expertise in distributed version control systems and DevOps tools, such as GitLab, Git, Linux, Docker, Podman, and Kubernetes.
  • Expertise in software development, with an emphasis on Python.
  • Proficiency in cloud computing (Azure, AWS, Google Cloud)
  • Proven experience leading the design, build, and deployment of complex and performant (reliable and scalable) software solutions in production.
  • Experience with ML frameworks like PyTorch for model training and inference.
  • Excellent written and verbal communication abilities.
  • Understanding of validation methods for ML models.
  • Skills in data preparation and corpus filtering using databases like PostgreSQL and MySQL.
  • Salary Note

    This estimate represents the typical salary range for this position based on experience and other factors (geographic location, etc.). Actual pay may vary. This job posting will remain open until the position is filled.

    Combined Salary Range

    USD $148,764.00 - USD $165,035.00 / Yr.

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