Robots and Pencils

Production-ready AI implementations for enterprises

Staff ML Engineer - AWS Trainium, SageMaker

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeRemote in CanadaNo salary listedRemote

About the Job

Requirements

Strong hands-on PyTorch experience, ideally including distributed or multi-device training.
Production experience with Amazon SageMaker for training and/or inference.
Comfort working close to the hardware layer, understanding device-specific compilation and debugging issues caused by the accelerator rather than the model.
Solid Python fundamentals and comfort operating in a client-facing production engineering environment.

Responsibilities

Train and operate models on Amazon SageMaker using AWS Trainium compute.
Write and optimize PyTorch training code, understanding how it compiles and executes on Trainium, including NeuronCore architecture, compiler behavior, and memory and throughput tradeoffs.
Diagnose training run issues caused by the hardware, distinguishing data or code problems from compiler- or device-level problems.
Translate a request for a Trainium job into a working, cost-aware end-to-end training pipeline.
Tune distributed training runs for throughput and cost on SageMaker's training infrastructure.
Work directly with client and internal engineering teams to scope and deliver production training workloads.

Desired Qualifications

AWS Trainium or Inferentia (Neuron SDK) experience is a strong plus; candidates without it may be considered if they have deep PyTorch experience and a track record of quickly learning new hardware targets.

Robots & Pencils is an AWS Partner building production AI systems for enterprise clients who need real engineering, not proofs of concept that never ship. We work forward-deployed, embedded directly with client teams, solving the problems that are too new or too specialized for a typical vendor relationship to handle.

The Role
We're looking for an engineer who can operate and train models on Amazon SageMaker running on AWS Trainium, AWS's custom silicon built specifically for large-scale model training. This isn't a role where you call an API and wait. You'll be walking up the stack: understanding what a training request actually looks like at the Trainium hardware and compiler level, then carrying that understanding all the way up through PyTorch training code and into a production SageMaker pipeline.
PyTorch is the backbone of this work. If you know the framework deeply and you're comfortable reasoning about how your code actually behaves on custom accelerator hardware rather than treating it as a black box, this role is built around that skill set specifically.

What You'll Do

Train and operate models on Amazon SageMaker with AWS Trainium as the underlying compute
Write and optimize PyTorch training code with a real understanding of how it compiles and executes on Trainium (NeuronCore architecture, compiler behavior, memory and throughput tradeoffs)
Diagnose training run issues that show up specifically because of the hardware, not just the model, distinguishing a data or code problem from a compiler or device-level one
Translate a request for "a Trainium job" into an actual working, cost-aware training pipeline, end to end
Tune distributed training runs for throughput and cost on SageMaker's training infrastructure
Work directly with client and internal engineering teams to scope and deliver real production training workloads, not experiments that stay in a notebook

What You'll Bring

Strong, hands-on PyTorch experience, ideally including distributed or multi-device training
Production experience with Amazon SageMaker for training and/or inference
Comfort working close to the hardware layer: you understand device-specific compilation and can debug issues that are actually about the accelerator, not just the model
AWS Trainium or Inferentia (Neuron SDK) experience is a strong plus; if you don't have it yet but have deep PyTorch and a track record of picking up new hardware targets fast, we want to talk to you
Solid Python fundamentals and comfort operating in a client-facing, production engineering environment

About the Company

Robots and Pencils

Production-ready AI implementations for enterprises

Robots & Pencils provides enterprise AI engineering services. It builds production-ready AI systems that companies can deploy quickly, delivering measurable business impact in weeks rather than months. The team blends advanced engineering with human-centered design, combining “robots” (AI/engineering) with “pencils” (UX and product design) to create solutions that are both technically solid and easy to use. The company works with large enterprises across sectors including Consumer Products and Retail, Education, Energy, Financial Services, Healthcare, and Manufacturing, and operates with small, senior teams instead of large consulting firms. Its delivery centers span Canada, the U.S., Eastern Europe, and Latin America, making it a nimble alternative to traditional global system integrators. The goal is to help enterprises move quickly and confidently with AI initiatives, delivering solutions that are reliable, scalable, and aligned with real business needs.

Company size: 51-200
Company stage: Not listed
Total funding: Not listed
Headquarters: Calgary, Canada
Founded: 2009

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