Amazon Sr Applied Scientist Sponsored Products Brands 

Canada, Ontario, Old Toronto 

427393413

Key job responsibilities
• Design and develop a state-of-the-art Agentic service platform using advanced Gen AI/ML technologies that provide consistent, well-reasoned outcomes for advertiser guidance in a secure & reusable architecture, delivering low latency and secure advertiser experiences
• Lead business and science strategy and roadmap for the team
• Design and build agents to guide advertisers in conversational and non-conversational experience.
• Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO).
• Curate datasets and tools for MCP.
• Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails.
• Collaborate with peers across engineering and product to bring scientific innovations into production.
• Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications.
A day in the life• Highly analytical: You solve problems in ways that can be backed up with verifiable data. You focus on driving processes, tools, and statistical methods which support rational decision-making.
• Team obsessed: You help the team achieve results. You foster the creative atmosphere to let engineers innovate, while holding them accountable for making smart decisions and delivering results.
• Humbitious: You’re ambitious, yet humble. You recognize that there’s always opportunity for improvement and use introspection and feedback from teammates and peers to raise the bar for your team.
• Engaged by ambiguity: You're able to explore new problem spaces with unique constraints and thus non-obvious solutions; you’re quick to identify any gaps in the team and the right person to fill them to best deliver value to customers
• Passionate for staying current with the latest developments in AI technologies and applying those insights to real-world product challenges

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.