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This position was posted on April 21, 2026 and is likely no longer accepting applications. We've kept it here for historical reference. Check out the similar jobs below!

Gather AI, Inc. logo

Senior Machine Learning Engineer (Ops)

Job Overview

Location

Hyderabad, Telangana, India; Open to Remote (India)

Job Type

Full-time

Category

Software Engineering

Date Posted

April 21, 2026

Full Job Description

📋 Description

  • As a Senior Machine Learning Engineer (Ops) at Gather AI, you will own the infrastructure engine behind the company's machine learning platform, ensuring that sophisticated vision models transition from research to reliable, scalable production systems that power autonomous drone-based warehouse intelligence.
  • Day to day, you will migrate detection pipelines to cloud infrastructure, build and maintain GPU training and CI/CD pipelines, implement automated deployment strategies, construct a multi-tenant MLOps platform using orchestration tools, establish model registries, and instrument full-stack observability for ML services.
  • You will join an engineering team at the forefront of warehouse robotics, building systems that turn ML research into production-grade infrastructure at the intersection of machine learning, cloud systems, and real-world logistics, with a focus on operational excellence and first-principles thinking.
  • In this role, you will deepen your expertise in MLOps and cloud-native ML infrastructure, gain end-to-end ownership of ML lifecycle systems, and contribute directly to transformative supply chain technology with measurable physical-world impact.

Skills & Technologies

Python
AWS
Azure
GCP
Docker
Senior
Remote

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Gather AI, Inc. logo
Gather AI, Inc.
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About Gather AI, Inc.

Gather AI builds autonomous drone inventory monitoring systems for warehouses. Drones fly predetermined routes, capture barcode and location data, and send real-time counts and images to a cloud dashboard. Machine-learning algorithms detect misplaced, missing, or mislabeled pallets and generate exception reports. The system integrates with WMS, ERP, and RFID platforms, eliminating manual cycle counts and reducing labor costs. Founded in 2017 as a Carnegie Mellon spin-out, the company serves 3PL, retail, and manufacturing facilities across North America.

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