Machine Learning Architect (AWS) - Canada

Rackspace Technology • Toronto, ON, Canada • 3h ago

Key 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.

Qualifications:

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.

Travel:

As per business requirements

Rackspace Technology

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