Rackspace Technology is looking to build AI and ML solutions for their customers and needs an ML Engineer to help build Data Science and AI/ML solutions at scale, working with mid-tier technologies that include application integration, security, and automation.
Requirements
- Experience in machine learning, data engineering, or software development roles (internships or academic projects acceptable).
- Solid understanding of supervised learning, classification, and data preprocessing techniques.
- Experience with data engineering concepts, including SQL, PostgreSQL, and REST API integration
- Basic knowledge of data ingestion and transformation concepts.
- Proficiency in Python and common ML libraries (e.g., scikit-learn, pandas, NumPy, TensorFlow or PyTorch).
- Familiarity with full-stack or web-based ML applications (e.g., React, Django, or Android Studio projects).
- Experience with version control tools like Git.
Responsibilities
- Assist in developing, training, and validating machine learning models for real-world applications (e.g., classification, prediction, and recommendation systems).
- Build and maintain data ingestion pipelines from structured and unstructured sources using Python and SQL-based tools
- Perform data cleaning, normalization, and feature engineering to prepare high-quality datasets for ML training and evaluation.
- Collaborate on ML projects such as outcome prediction systems, image classification models, and intelligent search interfaces.
- Contribute to building interactive applications by integrating ML models into frontend/backend systems (e.g., React, Django, REST APIs).
- Participate in MLOps workflows, including model versioning, basic deployment tasks, and experiment tracking.
- Document data flows, ML experiments, and application logic consistently.
Other
- Work Location: Remote
- Attend Agile meetings and collaborate with peers through code reviews and sprint activities.
- Strong problem-solving skills and attention to detail.
- Effective communication and documentation skills.
- Enthusiasm for learning new tools and growing within a collaborative team environment
