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Founding Machine Learning Engineer

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Adaptive Security

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Location:
United States , NYC

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

We are seeking a Staff ML Engineer to define and build Adaptive's ML capabilities. Adaptive is an AI cybersecurity company whose products use LLMs and ML models to detect, classify, and respond to threats in real time. ML is central to the future of our products, and we need someone who can own the strategy, infrastructure, and execution for how we use it. We don't have dedicated ML infrastructure or an ML team today. You'll be building this from the ground up. You'll set the technical direction for how we use ML across the company, stand up the infrastructure, and do the hands-on work yourself.

Job Responsibility:

  • Define Adaptive's ML strategy: where ML should be applied across our products, what infrastructure we need, and how we should approach build vs. buy decisions
  • Design and build production ML systems end-to-end — data pipelines, model training, evaluation frameworks, and inference serving
  • Establish evaluation methodology
  • Define how we measure model quality, catch regressions, and make data-driven decisions about model changes
  • Own the strategy for getting the data you need, in the format you need it — what/how to label, how to build feedback loops, and how our models improve over time
  • Partner with product engineers to integrate ML into the product
  • Write production code and work within our existing codebase
  • Over time, help build and lead the ML team as scope grows

Requirements:

  • 8+ years of experience building ML systems in production
  • Experience standing up the ML function at an early stage startup or as the senior or lead ML person at a previous company
  • Strong software engineering fundamentals
  • Write production-quality code in modern languages (Python, Java, TypeScript)
  • Work within large codebases
  • Experience with cloud ML infrastructure (AWS SageMaker, Bedrock, Modal, Baseten, or similar)
  • Experience with common ML and data processing frameworks (PyTorch, Tensorflow, Spark)
  • Comfortable working across the stack — infrastructure, backend services, and data systems
  • Track record of mentoring MLEs and other engineers with observable, clear improvements in those you've worked with
  • High autonomy

Additional Information:

Job Posted:
February 18, 2026

Employment Type:
Fulltime
Work Type:
On-site work
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