machine learning engineer

No description

• Design, develop, and deploy machine learning models to solve complex business challenges;
• Collaborate with cross-functional teams to understand requirements, define data pipelines, and deliver high-impact AI solutions;
• Implement, optimize, and maintain ETL processes for efficient data ingestion, transformation, and management;
• Use Python and relevant libraries to develop clean, efficient, and reusable code for AI and machine learning applications;
• Continuously monitor, evaluate, and improve the performance and accuracy of deployed models;
• Communate technical concepts clearly and effectively with technical and non-technical stakeholders;
• Document processes, methodologies, and model decisions to ensure transparency and reproducibility.

• Expert-level proficiency in machine learning techniques and algorithms;
• Advanced programming skills in Python and its data science ecosystem, including NumPy, pandas, and scikit-learn;
• Hands-on experience designing and managing ETL workflows in production environments;
• Strong understanding of data preprocessing, feature engineering, and model evaluation metrics;
• Excellent written and verbal communication skills; ability to convey complex ideas succinctly;
• Ability to collaborate and thrive in remote, distributed team settings;
• Track record of delivering robust, scalable machine learning solutions in real-world contexts;
• Nice to have: experience with cloud platforms for AI/ML such as AWS, GCP, or Azure; experience deploying models in production environments using Docker, Kubernetes, or MLflow; advanced degree in Computer Science, Data Science, or a related field.

• Contract employment.