ML Engineer I

Cleo - Richmond, VA

Full-time - Entry Level

Richmond, VA

1,001-5,000 employees

Paper Manufacturing

About the position

The Machine Learning Engineer I at Cleo is responsible for developing, implementing, and productizing machine learning models that deliver business value. This role focuses on transforming machine learning prototypes into scalable, production-grade solutions, working closely with data scientists, software engineers, and product teams to ensure effective integration of AI/ML models into products and services.

Responsibilities

• Productize ML Models: Work alongside data scientists to take machine learning prototypes from concept to production-ready solutions.
• End-to-End Model Deployment: Deploy machine learning models into production environments, ensuring reliability and maintainability, including CI/CD practices.
• Data Preparation and Feature Engineering: Preprocess, clean, and transform data for production-grade machine learning models.
• Collaborate with Product Teams: Support product managers in defining model requirements and aligning with product goals.
• Model Optimization and Scaling: Optimize machine learning models for performance and scalability in production environments.
• Build and Maintain ML Pipelines: Automate model training, testing, and deployment using DevOps principles.
• Monitoring and Maintenance: Monitor deployed models for performance drift and implement necessary updates.
• Model Evaluation and Reporting: Evaluate model performance, analyze metrics, and suggest improvements.
• Documentation and Best Practices: Document model deployment processes and best practices.
• Stay Current: Learn about emerging trends in AI/ML technologies and apply new methods.

Requirements

• 0-2 years of experience in machine learning engineering or a related field.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
• Basic understanding of machine learning algorithms, deployment practices, and integration.
• Some exposure to integrating machine learning models into products or production systems.
• Passion for AI/ML and a desire to contribute to solving business problems through machine learning.
• Familiarity with DevOps practices in model deployment, including CI/CD pipelines, version control, and automated testing.

Benefits

• Competitive compensation
• Great Healthcare + Dental + Vision
• Flexible PTO
• Culture of support, encouraging Life-Work balance
• 401k match
• FSA and HSA options
• Employee Assistance Program
• Paid Parental Leave
• Accelerated title and salary growth potential
• A fun and energetic work environment