Machine Learning Architect

Summary

Join Rackspace Technology's expanding team of motivated technologists as a Machine Learning Architect. You will be responsible for designing and executing machine learning projects, working directly with customers to understand their needs and build AI/ML solutions at scale. This role combines responsibilities as a Professional Services Machine Learning Architect and a hands-on Machine Learning engineer. You will need to demonstrate strategic thinking, technical expertise, and strong communication skills. The ideal candidate will have a proven track record of delivering results and a passion for machine learning. This is a remote position.

Requirements

• Masters with 10+ years of experience or PhD with 6+ years of experience in Machine Learning, Natural Language Processing (NLP) and Deep Learning
• Minimum 5+ years of experience architecting and building Machine Learning solutions
• Minimum 5+ years of experience with cloud platforms (AWS, GCP, Azure)
• Experience building ML models and strong knowledge of ML techniques is required
• Experience with hugging face, TensorFlow/pytorch, transformer architectures, prompt engineering, agentic systems, LLMs
• Strong coding experience in Python and architectural patterns like microservices
• Solid understanding of agile methodologies and experience in planning machine learning projects from inception to production deployment
• Strong problem-solving skills and the ability to lead a team on “what’s next” when encountering a technical issue in a machine learning project
• Excellent communication and presentation skills, with the ability to explain complex technical concepts to both technical and non-technical audiences

Responsibilities

• Design machine learning solutions and execute machine learning projects end to end from proof-of-concept stage to deployment in production using cloud native technologies and state of the art machine learning models
• Be technically focused but work directly with the business representatives/customers to understand the requirements driving the need for a solution to be developed
• Be responsible for all phases of the project from problem definition, data annotation, model development, model deployment to end user documentation/training
• Design the architecture of ML solutions on cloud platforms (AWS, Azure, GCP) including MLOPs
• Stay abreast of the latest developments. Read the latest published machine learning research and adapt the models to solve customer’s problems
• Establish credibility by demonstrating technical excellence and delivering value through solutions you build. Develop strong relationships with our customers

Benefits

Remote work