Data Science Engineer I - US
Job Description
Rackspace, a leading multicloud solutions expert, is seeking a Data Science Engineer I to join their innovative team. This entry-level position offers an exciting opportunity to work on cutting-edge AI and ML solutions while contributing to a company known for its expertise in end-to-end cloud solutions.
The role combines hands-on machine learning engineering with data pipeline development, making it perfect for candidates passionate about both ML and software engineering. You'll be working remotely with the option for hybrid work in San Antonio, focusing on building and deploying ML models, creating data pipelines, and integrating solutions into production systems.
Key aspects of the role include developing ML models for real-world applications, working with Python and SQL-based tools, and participating in the full ML lifecycle from data preparation to model deployment. You'll be using modern tools and technologies including Python, PostgreSQL, React, and various ML frameworks while working in an Agile environment.
The position offers competitive compensation ranging from $69,900 to $119,460, depending on location and experience. Rackspace is known for its strong company culture, consistently being recognized as a best place to work by Fortune, Forbes, and Glassdoor.
This role is ideal for recent graduates or early-career professionals with a strong foundation in machine learning and software engineering principles. You'll have the opportunity to work on diverse projects, from prediction systems to image classification models, while growing your skills in a collaborative team environment.
The company emphasizes professional growth and learning, making it an excellent starting point for a career in ML engineering. You'll be part of a team that embraces technology and innovation while working on solutions that directly impact customers across various industries.
Responsibilities For Data Science Engineer I - US
- Develop, train, and validate machine learning models for real-world applications
- Build and maintain data ingestion pipelines using Python and SQL-based tools
- Perform data cleaning, normalization, and feature engineering
- Collaborate on ML projects including outcome prediction systems and image classification models
- Contribute to building interactive applications by integrating ML models
- Participate in MLOps workflows
- Document data flows, ML experiments, and application logic
- Attend Agile meetings and collaborate with peers through code reviews
Requirements For Data Science Engineer I - US
- Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or related field
- Experience in machine learning, data engineering, or software development
- Solid understanding of supervised learning, classification, and data preprocessing techniques
- Experience with data engineering concepts, including SQL, PostgreSQL, and REST API integration
- Proficiency in Python and common ML libraries
- Familiarity with full-stack or web-based ML applications
- Experience with version control tools like Git
- Strong problem-solving skills and attention to detail
- Effective communication and documentation skills
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