Senior Machine Learning Engineer

MixMode

Completely RemoteFull TimeInformation Technology
Posted Today

Job description

Responsibilities

  • Design and operate production ML systems for large-scale, streaming data
  • Own system reliability, performance, and observability in production environments
  • Improve the speed and reproducibility of model evaluation and iteration
  • Collaborate with researchers to productionize models and integrate them into distributed systems
  • Contribute to the evolution of existing ML systems and infrastructure to improve scalability, maintainability, and performance

Requirements

  • 5+ years of experience with Python in production environments
  • 5+ years of experience applying machine learning using libraries such as PyTorch, scikit-learn, pandas, etc.
  • Experience building and operating distributed systems in production (e.g., Kubernetes, microservices, streaming systems)
  • Experience improving systems for ML experimentation and evaluation
  • Experience with big data or streaming technologies (e.g., Spark, Flink, or similar)
  • Strong mathematical foundation (e.g., degree in Computer Science, Mathematics, Statistics, Physics, or related field)
  • Ability to travel to Santa Barbara, CA, a few times per year

Preferred Qualifications

  • Experience with JVM languages (Java, Scala, or Kotlin)
  • Experience with Javascript/Typescript

Benefits

  • Remote-First Work Culture
  • Healthcare (Medical, Dental, Vision, Accident)
  • Basic & Voluntary Life and AD&D
  • Flexible Spending Account (FSA)
  • 401(k) with Employer Match
  • Paid Holidays & Flexible Paid Time Off (PTO)

About the Company

MixMode is a leading provider of AI-powered cybersecurity solutions at scale, pioneering a patented third-wave, context-aware AI approach that automatically learns and adapts to dynamic environments.

Skills & tools

PythonPyTorchKubernetesSparkMachine Learning

What the team is looking for

Use this list as a quick fit check before you apply.

  1. 015+ years Python experience
  2. 025+ years ML experience (PyTorch, scikit-learn, pandas)
  3. 03Distributed systems experience (Kubernetes, microservices)
  4. 04Big data/streaming experience (Spark, Flink)
  5. 05Strong mathematical foundation
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