Machine Learning Engineer (Platform)

Artera
$140,000 - $180,000Remote

About The Position

Artera is an AI startup that develops medical artificial intelligence tests to personalize therapy for cancer patients. Artera is on a mission to personalize medical decisions for patients and physicians on a global scale. As a Machine Learning Engineer at Artera, you’ll work on the AI Platform team with a focus on establishing scalable and efficient pipelines for model training, model evaluation, and data processing. You’ll work closely with AI model developers, fellow machine learning engineers, and our platform engineering team. You’ll ensure that Artera’s model developers can rely on highly efficient, large-scale training regimes and deploy optimized models to production environments.

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
  • Candidates must be currently authorized to work either in the United States or in Canada without the need for current or future employment-based visa sponsorship.

Nice To Haves

  • 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

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.

Benefits

  • equity is a core component of our compensation
  • 401k matching
  • unlimited paid time off (PTO)
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