Staff ML Engineer – AWS Trainium & SageMaker

Robots & Pencils

New 🇺🇸 United States only Remote

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AI Job Summary

You'll train and operate machine learning models on Amazon SageMaker using AWS Trainium custom silicon, writing optimized PyTorch code while understanding hardware-level compilation and performance tradeoffs. The role requires deep PyTorch expertise, production SageMaker experience, and comfort debugging at the accelerator level rather than treating hardware as a black box. You'll work directly with client teams to build end-to-end training pipelines, diagnose hardware-specific issues, and tune distributed training for cost and throughput. Strong plus: prior Trainium or Neuron SDK experience.

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Job Description

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

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Role Staff ML Engineer – AWS Trainium & SageMaker
Experience 8-9 years
Work type Remote
Location United States

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Robots & Pencils

Enterprise Software · 500+ Members · Canada

Robots & Pencils is an applied AI engineering firm and AWS Advanced Tier Services Partner that builds generative and agentic AI on AWS.

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Job Overview

Eligibility

United States Hires remotely in the United States.

Workplace

Remote

Job Posted:

1 day ago

Job Type

Full Time

Experience

8-9 years

Staff ML Engineer – AWS Trainium & SageMaker

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