Senior / Staff Research Engineer, Generative Ai Deployment
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Senior / Staff Research Engineer, Generative AI Deployment
Customer & Solutions · Toronto, ON · Full-time · Senior levelThe posting shares only company background and no day to day duties, so this read leans on the job title and the company line. The title points to taking generative AI models out of research and making them run reliably inside the systems that train and test autonomous trucks and robotaxis. A strong candidate would combine research depth with solid engineering habits and a record of getting large models into real use.How it fits the AI eraGenerative AI sits at the center of this company's approach, since its driving software learns mostly in an AI built simulator. The work here is less about inventing a model and more about making it fast, stable and trustworthy at scale. People still decide what counts as safe, judge whether simulated worlds match the road, and own the tradeoffs when a model is not good enough.How it builds AI experienceSomeone in this role would likely gain hands on experience running generative models that create driving scenarios, and seeing them used in a safety focused product. To build toward it, practice deploying large models, speeding up how they run, and checking their output against clear measures of quality. A project that turns a research model into a dependable service would be a good proof point.Worth showingDeploying large generative modelsSpeeding up model inferenceShipping research into productionJudging simulation realismThis is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.About WaabiA Toronto company training self-driving trucks and robotaxis mostly inside its own AI-generated simulator, rather than by racking up millions of real road miles.
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Customer & Solutions · Toronto, ON · Full-time · Senior levelThe posting shares only company background and no day to day duties, so this read leans on the job title and the company line. The title points to taking generative AI models out of research and making them run reliably inside the systems that train and test autonomous trucks and robotaxis. A strong candidate would combine research depth with solid engineering habits and a record of getting large models into real use.How it fits the AI eraGenerative AI sits at the center of this company's approach, since its driving software learns mostly in an AI built simulator. The work here is less about inventing a model and more about making it fast, stable and trustworthy at scale. People still decide what counts as safe, judge whether simulated worlds match the road, and own the tradeoffs when a model is not good enough.How it builds AI experienceSomeone in this role would likely gain hands on experience running generative models that create driving scenarios, and seeing them used in a safety focused product. To build toward it, practice deploying large models, speeding up how they run, and checking their output against clear measures of quality. A project that turns a research model into a dependable service would be a good proof point.Worth showingDeploying large generative modelsSpeeding up model inferenceShipping research into productionJudging simulation realismThis is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.About WaabiA Toronto company training self-driving trucks and robotaxis mostly inside its own AI-generated simulator, rather than by racking up millions of real road miles.
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