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Job listing

RemoteNot Disclosed

Senior Machine Learning Engineer at High-growth AI-driven tech platform

Join a high-growth AI-driven tech platform as a Senior Machine Learning Engineer and lead the charge in building scalable, production-grade intelligence. This is a rare opportunity to work with top-tier VC backing and a world-class team, where you will have total ownership over the ML lifecycle. If you are passionate about deploying sophisticated models that solve real-world problems at scale while enjoying the flexibility of a remote environment, this role offers the perfect blend of technical challenge and massive impact.

Overview

Role overview

As a Senior Machine Learning Engineer, you will drive the development and deployment of sophisticated models that power core product features. You will collaborate with cross-functional teams to design scalable ML architectures, improve model performance, and implement automated pipelines. Your work will directly impact user experience by delivering intelligent, data-driven solutions at scale.

Company

About the company

High-growth AI-driven tech platform

Responsibilities

What you will do

  • Design, train, and deploy large-scale machine learning models to solve complex real-world challenges.
  • Optimize ML infrastructure and data pipelines to ensure high availability and low-latency inference.
  • Collaborate with product and engineering teams to integrate intelligent features into the core platform.

Candidate profile

Who this is a fit for

  • Proven experience building and scaling production machine learning systems in a cloud environment.
  • Strong proficiency in Python and deep learning frameworks like PyTorch or TensorFlow.
  • Deep understanding of MLOps principles, including versioning, monitoring, and automated deployment strategies.

What makes it remarkable

Why this role is remarkable

  • Work at the intersection of cutting-edge research and production-grade engineering within a rapidly evolving ecosystem.
  • Join a well-funded venture backed by top-tier VCs with a clear path toward market leadership.
  • Take ownership of end-to-end ML lifecycles with significant autonomy to shape technical strategy and infrastructure.

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