Remote Senior Machine Learning Engineer

Description:

• As a Senior Machine Learning Engineer at Wave, you will help shape the future of AI capabilities by combining traditional machine learning with cutting-edge Generative AI technologies.
• You will be responsible for developing, scaling, and maintaining production-grade ML models while applying innovative GenAI approaches to solve customer and business challenges.
• This role offers an opportunity to work with a modern, cloud-native data and AI stack, where traditional ML systems and emerging GenAI solutions coexist to deliver secure, reliable, and scalable AI services at Wave.
• You will collaborate with product and technical teams to develop and deploy both traditional ML models and GenAI systems.
• You will drive the automation and scalability of Wave’s MLOps stack, supporting the scaling of production-ready ML models.
• You will design and build GenAI proofs-of-concept (PoCs) and evaluate and deploy those that meet performance and business impact criteria into production.
• You will contribute to the development of a unified API to provide secure, scalable, and reliable access to AI models.
• You will monitor the reliability of all deployed models, enhancing their observability and explainability to meet ethical and regulatory standards.
• You will mentor other engineers, sharing best practices for model development, deployment, and monitoring in both traditional ML and GenAI contexts.
• At Wave, you will have the opportunity to continuously learn and grow by exploring cutting-edge ML frameworks and developing innovative GenAI projects.

Requirements:

• You must have 5+ years of experience in building and deploying production-grade machine learning systems.
• Strong Python and SQL skills are required, along with familiarity in containerization tools like Docker and an understanding of secure model access via APIs.
• Familiarity with AWS cloud services, including SageMaker, Amazon Bedrock, and Amazon Q is necessary.
• You should have experience automating MLOps pipelines and deploying models for both batch and real-time inference.
• Hands-on expertise in developing GenAI proofs-of-concept and taking them through to production is essential, as well as experience scaling traditional ML models for production at scale.
• A solid understanding of AI explainability, including experience with model interpretability techniques, observability, and monitoring to ensure performance and reliability is required.
• Familiarity with applying FinOps concepts to optimize cloud resources, reduce costs, and ensure the efficient scaling of AI models is important.
• You should have an appreciation for both the opportunities and challenges associated with Generative AI, including the ability to identify risks and manage ethical considerations.
• A collaborative mindset, with strong communication skills and a passion for mentoring and growing the capabilities of the ML team is essential.

Benefits:

• You will have the flexibility to work from home or in the welcoming, energizing office in Toronto.
• Wave invests in your health and wellness, considering body, mind, and soul in their benefits offerings.
• You will be supported in your professional growth with diverse learning experiences, educational allowances, and mentorship.
• Fair compensation and various office perks are provided, along with the expected benefits from a growing tech company.
• Wave promotes a diverse and inclusive culture, valuing individuality and encouraging everyone to bring their authentic selves to work.
• The company has been recognized as one of Canada's Top Ten Most Admired Corporate Cultures and one of Canada’s Great Places to Work in various categories.