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Description The AI Center of Excellence (AICE) builds AI primitives that power system-intrinsic intelligence and Trusted Intelligent Knowledge Infrastructure for both AI-as-a-Consumer and human users. We develop AI capabilities independently and in partnership with product-owning teams to evolve Amazon's AI-driven operations and productivity. Our impact is enterprise-broad and global. We are looking for a Machine Learning Engineer who can take an idea from experimentation to a hardened, reusable primitive ready for broad consumption across the enterprise. Key job responsibilities Own the end-to-end development of AI/ML primitives - from ideation and experimentation through architecture, implementation, testing, and production deployment Drive the integration of AICE primitives into partner products, collaborating closely with product-owning teams to ensure seamless adoption and value delivery Design, test, and harden primitives for general availability, enabling consumption by other teams and product owners across the organization Architect solutions suitable for production environments, maintaining best practices in reliability, scalability, observability, and operational excellence Contribute to AICE's mission of driving AI transformation through best practices in AI-driven development, implementation processes, and operationalization within your area of expertise Establish and evolve engineering standards that raise the bar for how AI primitives are built, tested, deployed, and maintained A day in the life Every day brings new challenges. You might design experimentation tooling to validate primitives, refine our codebase for operational excellence, or work through technical challenges with partners integrating AICE primitives into their products. Other days, you'll monitor production systems and support teams consuming our models. No two weeks look the same. You'll move fluidly between deep technical work and collaborative problem-solving - always with the goal of building AI primitives that are trusted, reliable, and impactful at enterprise scale. About The Team AICE is a team of scientists and machine learning engineers building the AI primitives that power Amazon's intelligent systems. We develop and harden reusable capabilities for broad consumption by product teams across the enterprise - and partner with those teams to integrate them. Basic Qualifications Experience programming with at least one software programming language Bachelor's degree or above in computer science 2+ years of non-internship professional software development experience Experience leading design teams in problem definition, artifact rendering, cross-functional collaboration and delivery, and user validation and measurement 1+ years of experience designing or architecting systems (design patterns, reliability, and scaling) for production AI/ML workloads 1+ years of experience building, hardening, and operationalizing AI/ML solutions - from experimentation through production deployment Strong foundation in traditional software development practices (code reviews, testing, debugging, version control, CI/CD) with the ability to also leverage AI-assisted development tools effectively Experience building reusable libraries, frameworks, or platform capabilities consumed by other engineering teams Preferred Qualifications 2+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience Master's degree in computer science or equivalent Experience in machine learning, data mining, information retrieval, statistics or natural language processing 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 - 114,800.00 - 191,800.00 CAD annually Company - Amazon Development Centre Canada ULC Job ID: A10468233
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.