Python Machine Learning Engineer

You will develop machine learning solutions from initial data pipelines through production deployment and monitoring. The work includes turning business goals into reliable machine learning systems and working with product, engineering, and business stakeholders.

You will use supervised and unsupervised learning, time-series forecasting, natural language processing, computer vision, and statistical modeling. You will also evaluate and improve models for accuracy, performance, and scalability.

The role includes staying current with machine learning advances and applying useful methods to improve results.

• Build data pipelines, model architectures, deployment workflows, and monitoring systems.
• Define problem statements and success metrics with product, engineering, and business teams.
• Apply data preprocessing, feature engineering, model tuning, and evaluation metrics.
• Design scalable, production-grade machine learning systems.

The role requires at least four years of hands-on data science or machine learning development experience, along with the education and technical skills below.

• Schedule: 20+ hours per week.
• Language: Professional fluency in English.
• Education: Bachelor's or master's degree in computer science, machine learning, artificial intelligence, statistics, or a related quantitative field.
• Experience: At least four years of hands-on data science or machine learning development experience.
• Core skills: Strong Python and proficiency with Pandas, NumPy, Scikit-learn, or comparable libraries.
• Technical knowledge: Data preprocessing, feature engineering, model tuning, evaluation metrics, and choosing suitable models for real-world use cases.