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Machine Learning Engineer – Production Systems

Anton Volkov

Full-time · Mid-level · New_York

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About the role

We run ML models in production serving millions of predictions per day and need an ML engineer who is as comfortable with systems and infrastructure as they are with model development. You will own the full model lifecycle.

Responsibilities

  • Develop and productionise ML models from research to serving
  • Build and maintain ML pipelines using Airflow and MLflow
  • Monitor model performance and handle drift detection
  • Work with research scientists to move experiments to production
  • Contribute to our ML platform and internal tooling

Requirements

  • 4+ years ML engineering with production deployment experience
  • Strong Python (PyTorch or TensorFlow) and MLOps tooling
  • Experience with model serving frameworks (TorchServe, Triton, or BentoML)
  • Familiarity with Kubernetes and Docker for ML workloads
  • Able to monitor and debug production model performance

Benefits

  • High-scale production environment
  • Full remote
  • Competitive salary + equity
  • GPU access for development
  • Engineering-led culture

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Categories

AI & Machine Learning Engineers data science & analytics data science

Skills

python pytorch tensorflow docker kubernetes

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Job Type

Full-time

Level

Mid-level

Language

English

Salary Range

$130,000 – $170,000

AI Expertise

AI & Machine Learning Engineers data science & analytics data science

Skills

python pytorch tensorflow docker kubernetes mlflow airflow

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