Machine Learning Engineer – Production

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and create scalable machine learning systems for both real-time and batch inference.

• Construct model deployment pipelines utilizing containerization and Continuous Integration/Continuous Deployment (CI/CD).

• Develop APIs and services aimed at serving machine learning models.

• Implement monitoring and alerting mechanisms for model performance, drift, and data quality.

• Work in conjunction with Data Engineers to ensure dependable feature pipelines.

• Oversee model versioning, reproducibility, and governance.

• Enhance inference performance and optimize cloud cost efficiency.

• Assist in retraining workflows and ongoing improvements.

• Ensure adherence to security and compliance standards for both data and models.

⛳️ Requirements

• Over 4 years of experience in Machine Learning Engineering or Applied Machine Learning.

• Proficient programming skills in Python.

• Practical experience with PyTorch, TensorFlow, or similar frameworks.

• Experience in deploying models into production, whether API-based, batch, or streaming.

• Familiarity with Docker and containerized ecosystems.

• Knowledge of Kubernetes for scaling machine learning services.

• Experience with MLOps tools such as MLflow, model registry, and CI/CD integration.

• Strong comprehension of feature engineering and data preprocessing.

• Experience in working with AWS, Azure, or GCP environments.

• Awareness of monitoring, logging, and observability tools.

🏝️ Benefits

• Remote Job