Role overview

Machine Learning Engineer (AI Platform Lead)

Requirements and responsibilities

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Essential Responsibilities:

  • Accountable for Artera’s ML compute infrastructure including scaling up Artera’s Foundation Model development by developing distributed training infrastructure and developer libraries.
  • Build and evolve the core libraries used by AI scientists to develop, launch, and monitor AI products.
  • Work with model developers to optimize GPU and CPU efficiency and data throughput of large-scale foundation models and downstream model training runs.
  • Optimize Artera’s ability to store and serve terabytes of digital pathology data efficiently for the use in serving large-scale training regimes.
  • Ensure that Artera’s observability infrastructure provides a clear picture of how to continue to optimize performance across our model landscape.

Experience Requirements:

  • 5+ years of industry software engineering experience
  • 4+ years of industry experience using one of PyTorch, TensorFlow, or JAX in Python
  • 3+ years of industry experience building with AWS, Docker, and Kubernetes
  • 1+ years of industry experience optimizing large-scale, high data-throughput, distributed machine learning training pipelines

Desired:

  • Experience in using ML orchestration frameworks such as Flyte, Ray, Kubeflow, Metaflow, MLFlow, Dagster, Argo Workflow or Prefect
  • Experience using Terraform, SqlAlchemy
  • Experience in multi-node and multi-gpu training.
  • Experience deploying and maintaining infrastructure for machine learning training and production inference
  • Familiarity with TorchScript, ONNXRuntime, DeepSpeed, AWS Neuron or similar approaches to inference optimization

Work Authorization Requirement:

  • This is a remote role open to candidates who are currently authorized to work either in the United States or in Canada without the need for current or future employment-based visa sponsorship. Artera does not sponsor visas for this position.
  • Eligible candidates may include:
  • Individuals authorized to work in the United States on a permanent basis (e.g., U.S. citizens, U.S. permanent residents), or
  • Individuals authorized to work in Canada (e.g., Canadian citizens or Canadian permanent residents).
  • Visa Transfers (if needed).

Here are few posts from our teammates, partners and customer voices to highlight the work we do:

  • Artera Shapes the Future of Cancer Treatment Using Machine Learning on AWS
  • How Artera AI test allowed Bruno to avoid hormone therapy
  • Startups are using AI to predict responses to Cancer Drugs
  • ArteraAI validates its Prognostic Model in Advanced Prostate Cancer
  • How Artera Enhances Prostate Cancer Diagnostics Using AWS
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Browse stack
FocusMachine Learning EngineeringRole area
Seniority signalSeniorCandidate level
StackAWS, Docker, KubernetesPrimary skills
Location2 accepted countriesEligibility

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