Manager, MLOps Engineering - (Remote - Canada)

## Full Description

Jobgether has ALL remote jobs globally. We match you to roles where you're most likely to succeed, and provide feedback on every application to help you learn. No more guesswork, application black holes, or recruiter ghosting in your job search.

For one of our clients, we are looking for a Manager, MLOps Engineering, working remotely from Canada.

As a Manager, MLOps Engineering, you will lead ateam responsible for developing and maintaining a cutting-edge machine learning infrastructure. Your role will involve collaborating with data scientists, engineers, and product teams to build scalable MLOps solutions that enhance machine learning and generative AI capabilities. You will oversee the deployment of machine learning models, optimize processes for continuous integration, and support the development of AI-powered features for customers. This role requires strong technical leadership, hands-on experience with cloud-based MLOps, and a deep understanding of modern AI and deep learning technologies.

Accountabilities:

• Lead and mentor a team of Machine Learning Engineers to implement and scale MLOps solutions.
• Work closely with Data Science and Engineering teams to develop production-ready AI features.
• Design and maintain infrastructure for rapid ML prototyping, continuous deployment, and model evaluation.
• Support and improve AI platforms for both pre-trained and custom-trained models.
• Plan and manage large-scale AI projects while educating stakeholders on ML best practices.

Requirements

• 5+ years of experience in MLOps or Machine Learning Engineering.
• Proven experience in leading ML projects and mentoring engineering teams.
• Expertise in deploying machine learning models in production environments.
• Strong programming skills in Python, with experience in ML frameworks such as scikit-learn, pandas, and XGBoost.
• Hands-on experience with deep learning and generative AI models.
• Proficiency with cloud platforms, preferably AWS and SageMaker.
• Familiarity with containerization technologies like Docker and Kubernetes.

Benefits

• Competitive salary and performance-based bonuses.
• Fully remote work with flexible scheduling.
• Opportunity to work with cutting-edge AI and ML technologies.
• Career growth and professional development opportunities.
• Inclusive and diverse work environment.

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