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Senior Engineer - Coach (AI) Canada Jobs (Remote work)

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Senior Machine Learning Engineer, Central AI
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Join Atlassian's Central AI team to revolutionize AI across all products. Develop and scale cutting-edge machine learning models using Python/Java, Spark, and cloud platforms. Collaborate with cross-functional teams in Canada to build robust AI infrastructure and deliver cohesive user experiences.
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Canada , Canada
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Not provided
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Atlassian
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Until further notice
Senior Software Engineer, Backend (AI Agent)
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Join Cresta's AI Agent team in Toronto to build scalable backend systems for cutting-edge AI solutions. We seek a Senior Backend Engineer with 5+ years' experience in cloud architecture, APIs (gRPC/REST), and Kubernetes. You'll design reliable, high-performance server infrastructure for real-worl...
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Canada , Toronto
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Cresta
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Until further notice
Senior Engineering Manager, Core AI Platform
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Lead the Core AI Platform team at Dropbox, managing 12-20 engineers to build and integrate cutting-edge AI capabilities. This senior role requires 8+ years of engineering management and 10+ years of technical experience, with a strong background in AI products and platform development. Drive high...
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Canada
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200600.00 - 271400.00 CAD / Year
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Dropbox
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Until further notice
Senior Machine Learning Engineering Manager, Gen AI
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Lead the development of Dropbox's AI product, Dash, as a Senior Machine Learning Engineering Manager. You will guide a team in Gen AI, NLP, and LLM to drive product growth and monetization. This role in Canada requires 10+ years of experience, including 5+ in management, and expertise in real-wor...
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Canada
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219300.00 - 296700.00 CAD / Year
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Dropbox
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Until further notice
Explore Senior Engineer - Coach (AI) jobs and discover a pivotal role at the intersection of advanced software engineering, artificial intelligence, and mentorship. This unique hybrid position is designed for seasoned technical experts who not only architect and build sophisticated AI systems but also elevate entire teams through coaching and leadership. Professionals in this field are instrumental in translating cutting-edge AI research, particularly in generative AI and autonomous agentic systems, into robust, scalable, and reliable production applications that drive tangible business value. Typically, a Senior Engineer - Coach (AI) shoulders a dual set of responsibilities. On the technical side, they are responsible for the end-to-end lifecycle of AI platforms. This involves designing and implementing the architecture for high-throughput, distributed systems that power intelligent agents capable of planning, reasoning, and executing complex tasks. They develop and maintain APIs and services that enable multi-channel interactions, ensuring low latency, high accuracy, and operational reliability at scale. A critical part of their role is establishing rigorous MLOps practices, including observability, monitoring, model governance, and continuous evaluation frameworks to maintain system performance and control issues like hallucination in generative models. Beyond hands-on engineering, the "Coach" aspect defines this career path. These individuals act as technical guides and multipliers. They define technical strategy and roadmaps, make critical decisions on technology stacks, and set architectural standards for AI development across the organization. They mentor and upskill other engineers and data scientists, fostering best practices in software craftsmanship, system design, and AI implementation. They collaborate closely with cross-functional teams, including product managers and AI researchers, to align technical execution with business objectives, often articulating complex technical concepts to diverse stakeholders. The typical profile for these senior roles requires a substantial background in software engineering, often 8+ years, with a significant portion dedicated to AI/ML systems. Expertise in modern programming languages like Python, Go, or Java is essential, coupled with deep experience with cloud platforms (AWS, Azure, GCP), containerization, and CI/CD pipelines. A strong foundational understanding of AI principles—including large language models (LLMs), retrieval-augmented generation (RAG), agent frameworks, and machine learning—is mandatory. Crucially, successful candidates demonstrate exceptional problem-solving abilities, comfort with ambiguity, and outstanding communication and leadership skills. A degree in Computer Science, AI, or a related quantitative field is common, with advanced degrees often preferred. For those seeking to lead the future of autonomous systems while developing technical talent, exploring Senior Engineer - Coach (AI) jobs represents a career-defining opportunity at the forefront of technology.

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