AmazonApplied Scientist, Amazon Canada Technology, Amazon Canada
Amazon is hiring an Applied Scientist, Amazon Canada Technology, Amazon Canada in Vancouver, Canada. It pays CAD 149k-CAD 249k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Builds AI ●●●● is how Level rates this applied scientist role: the job is building AI systems.
- The posting mentions Python, PyTorch and LLMs among its tools and skills.
- Level classes it as a senior role.
- Amazon has 21,000+ other open roles on Level.
- Posted in the last few days.
AI in this role
Develop and train reasoning LLMs and multi-objective optimization systems to power localized search and recommendation for the Canadian market.
We are hiring an Applied Scientist to join Amazon Canada Technology and push the science boundaries for Canada: the reasoning LLMs, embedding models, cross-encoder rankers, and multi-objective optimization systems that turn billions of products into the right answer for hundreds of millions of Canadian customers. The role spans the full model lifecycle, from understanding and deciphering where the problem lies, building models, mid-training reasoning models on data such as shopping, returns, reasoning, localization to aligning the models with customers on dimensions that matter for shopping through fulfillment. You will be a pioneer on this team and will own defining the long-term Science strategy and execute on the same by partnering closely with several partner teams such as Core Search, Returns and work with CA Product Managers, Software Engineering and BI/DEs.
Key job responsibilities
• Develop personalized multi-modal thinking-LLM techniques that reason about customers, search, queries, ranking and products across both primary and secondary languages.
• Train large language models on various data signals and sets: domain-adaptive continued pre-training, reinforcement learning shopping reasoning traces, instruction tuning for natural-language shopping queries.
• Analyze Canada (CA) ranking-quality gaps using offline metrics and benchmark CA model staleness and architecture against other marketplace (e.g. US, EU, JP) equivalents.
• Formulate falsifiable ranking hypotheses linking a specific feature, architecture, or training change to predicted metric movement.
• Run standardized offline evaluation of model candidates; validate feature statistical distributions and coverage in-locale to detect anomalies; own and lead experiments to drive improvements on offline and online experiment benchmarks.
• Lead error analysis on failing query segments and segment-level deep dives (head/torso/tail, category, device), surfacing CA-specific failure modes such as bilingual and thin-category gaps.
• Own metric-tradeoff analysis and acceptable-regression boundaries, bridging model behavior and CA business priorities.
• Partner with teams such as Core Search on hypotheses, model training, and quality gates (MTBR / WLBR / SSAI).
• Classify feature-expansion effort tiers (available / pipeline extension / locale training / infeasible) combining locale knowledge with science judgment.
About the team
Amazon.ca Technology builds the products and services millions of Canadians rely on every day. Our teams tackle challenges unique to the Canadian market while contributing to Amazon initiatives that span the globe — giving you the best of both worlds: meaningful local impact and the scale of global tech. If you want to help shape Canada's digital commerce landscape within a collaborative Canadian work culture, this is the place to do it.
Basic qualifications
- 3+ years of building models for business application experience
- Experience in CS, CE, ML or related field
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred qualifications
- Experience using Unix/Linux
- PhD, or a Master's degree and experience in CS, CE, ML or related field
- Experience in understanding performance metrics and developing them to measure progress against key performance indicators
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.
CAN, BC, Vancouver - 149,300.00 - 249,300.00 CAD annually
CAN, ON, Toronto - 149,300.00 - 249,300.00 CAD annually
How we rate this
Applied Scientist, Amazon Canada Technology, Amazon Canada at Amazon rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in applied scientist jobs at this level
Pay
- Typical applied scientist job
- $172k
Use the typical applied scientist figure as a reference when pay comes up. See applied scientist jobs
Questions you could be asked
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where deep learning was part of your work. What did you do?
- Tell me about a project where natural language processing was part of your work. What did you do?
- Tell me about a project where information retrieval was part of your work. What did you do?
- Tell me about a project where experimentation was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Machine learning, Deep learning, Natural Language Processing, Information Retrieval, and Experimentation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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