Machine Learning Engineer - Remote

Overview

We are seeking an experienced Machine Learning Engineer to join our team, responsible for the end-to-end lifecycle of machine learning systems, from designing, training, and deploying ML models for production use cases to developing robust data pipelines.

In Short

• Design, train, and deploy machine learning models for production use cases.
• Develop data pipelines for preprocessing, feature engineering, and model serving.
• Implement MLOps best practices: CI/CD for ML, monitoring, retraining workflows, and model lifecycle management.
• Build and validate ML Proof of Concepts (POCs) for new business opportunities.
• Optimize models for performance, scalability, and efficiency.
• Collaborate with data engineers, DevOps, and product teams for integration.
• Stay updated with new ML/AI research and tools.

Requirements

• Proven experience building and deploying ML systems in production.
• Strong proficiency in Python (Pandas, NumPy, Scikit-Learn, XGBoost, PyTorch/TensorFlow, Jupyter).
• Knowledge of SQL, Spark and data manipulation.
• Familiarity with MLOps tools (MLflow, SageMaker, or Vertex AI).
• Hands-on experience with cloud platforms (AWS, GCP, or Azure).
• Strong understanding of software engineering best practices.
• Nice to have: experience with feature stores, time series modeling, or generative AI techniques.

Benefits

• Opportunity to work on innovative projects.
• Collaborative team environment.
• Flexible working hours.
• Access to the latest technologies and tools.
• Professional development opportunities.