Machine Learning Operations Engineer

About Us:

Redshred is a leading innovator in making document-based content accessible for downstream integration and innovation through the creative use of AI and ML.

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Job Responsibilities:

• Design and Implement ML Pipelines: Develop, deploy, and maintain scalable ML pipelines for various machine learning models and applications.
• Automation and Optimization: Automate data collection, preprocessing, model training, and deployment processes. Optimize performance for both training and inference.
• Infrastructure Management: Manage and maintain cloud-based infrastructure and services for ML operations (AWS, GCP, Azure, etc.).
• Model Monitoring: Implement and manage monitoring solutions to ensure the reliability and accuracy of deployed models.
• Collaboration: Work closely with data scientists, software engineers, and other stakeholders to integrate ML models into production systems.
• Security and Compliance: Ensure that all ML operations comply with relevant security, privacy, and regulatory standards.
• Continuous Improvement: Stay updated with the latest developments in ML Ops and propose improvements to current processes and technologies.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience: 3+ years of experience in ML, ML Ops, DevOps, or related fields.
• Technical Skills:
  • Proficiency in Python, Docker, Kubernetes, and Terraform.
  • Experience with ML frameworks such as TensorFlow, PyTorch, or similar.
  • Knowledge of CI/CD tools and practices.
  • Familiarity with one or more cloud platforms (AWS, GCP, Azure).
• Soft Skills:
  • Strong problem-solving abilities and analytical thinking.
  • Excellent communication and collaboration skills.
  • Ability to work independently and as part of a team.
• Other Requirements: US citizenship is required.

Benefits:

• Health Insurance: Comprehensive health, dental, and vision insurance plans.
• 401K: Competitive 401K matching program.
• PTO: Unlimited paid time off to support work-life balance.
• Remote work: Remote work is available, with a bias towards candidates in the DC metro area who could come into HQ for design discussions and hackathons.
• Professional Development: Opportunities for continuous learning and professional growth.

Work Environment:

Flexible working hours and a collaborative, inclusive work culture.