Machine Learning Engineer | Remote

Crossing Hurdles; La Réunion; Sur place; EUR 75 000 - 120 000; Plein temps

Résumé du poste

Crossing Hurdles is seeking an experienced machine learning engineer to design, develop, and deploy ML models solving complex business challenges. You will collaborate with cross-functional teams to define data pipelines and deliver AI solutions, while implementing robust ETL workflows and maintaining production-grade code.

You will work with Python and its data science ecosystem to build clean, reusable solutions, continuously monitor model performance, and document decisions for transparency

Qualifications

• Expert-level proficiency in machine learning techniques and algorithms.
• Advanced Python programming and data science ecosystem (NumPy, pandas, scikit-learn).
• Hands-on experience designing and managing ETL workflows in production.
• Strong understanding of data preprocessing, feature engineering, and model evaluation metrics.
• Ability to collaborate in remote, distributed teams.

Responsabilités

• Design, develop, and deploy ML models to address complex business challenges.
• Collaborate with cross-functional teams to gather requirements and define data pipelines.
• Implement, optimize, and maintain ETL processes for data ingestion and transformation.
• Create clean, reusable Python code for AI and ML applications.
• Continuously monitor and improve model performance and accuracy.
• Document processes, methodologies, and model decisions for transparency.

Connaissances

Machine Learning Expertise

Python Proficiency

Data Preprocessing

Feature Engineering

Model Evaluation

Remote Collaboration

Outils

NumPy

pandas

scikit-learn

Description du poste

• Design, develop, and deploy machine learning models to address complex business challenges.
• Collaborate with cross-functional teams to gather requirements, define data pipelines, and deliver impactful AI solutions.
• Implement, optimize, and maintain ETL processes for efficient data ingestion, transformation, and management.
• Utilize Python and relevant libraries to create clean, efficient, and reusable code for AI and machine learning applications.
• Continuously monitor, evaluate, and enhance the performance and accuracy of deployed models.
• Document processes, methodologies, and model decisions to ensure transparency and reproducibility.

Requirements

• Have expert-level proficiency in machine learning techniques and algorithms.
• Possess advanced programming skills in Python and its data science ecosystem, including libraries such as NumPy, pandas, and scikit-learn.
• Have hands‑on experience designing and managing ETL workflows in production environments.
• Have a strong understanding of data preprocessing, feature engineering, and model evaluation metrics.
• Demonstrate a proven ability to collaborate and thrive in remote, distributed team settings.