Full-Time AI/Machine Learning Engineer

• Key Responsibilities
• Design, develop, and implement end-to-end Machine Learning pipelines for training, testing, and deployment of predictive models.
• Work closely with Data Scientists to translate prototypes and models into scalable, production-grade code (MLOps).
• Develop robust, efficient, and well-documented code primarily using Python and relevant ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Implement monitoring and alerting solutions for models in production to track performance, detect drift, and ensure reliability.
• Collaborate with Data Engineers to ensure efficient data preparation, feature engineering, and access to necessary data infrastructure.
• Stay current with the latest advancements in AI, ML techniques, and scalable infrastructure.
• Skills:
• 3+ years of professional experience in a Machine Learning Engineer, AI Developer, or similar role.
• Strong expertise in Python and object-oriented programming.
• Practical experience with major Machine Learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn).
• Solid understanding of MLOps principles and the tools required for model deployment, versioning, and lifecycle management (e.g., MLflow, Kubeflow, or similar).
• Proficiency in SQL and experience working with large datasets and data warehousing concepts.
• Excellent analytical and problem-solving skills.
• Highly Valued Skills:
• Experience working with Cloud platforms (AWS, GCP, or Azure).
• Knowledge of containerization technologies (Docker, Kubernetes).
• Familiarity with distributed computing frameworks (e.g., Spark).
• Advanced degree (M.S. or Ph.D.) in Computer Science, Engineering, or a related quantitative field.
• Very good level of English, both spoken and written.

What is the last date for applying to the job?

Which countries are accepted for this remote job?