Tech Stack

Description

You will design and build platforms that support computer vision and ML workloads at scale, enabling ML teams with well-designed infrastructure and tooling. Your work will help create intelligent machinery for agriculture and construction, solving monumental problems for customers.

Requirements

• Strong technical judgment with ability to evaluate and improve existing platform systems
• Experience with compute orchestration (Kubernetes, Slurm) and cloud platforms (AWS preferred)
• Background in DevOps or platform engineering with experience in ML-adjacent systems
• Hands-on engineering skills with ability to influence platform direction through collaboration
• Experience supporting distributed training and inference systems (e.g., Ray)

Responsibilities

• Design, build, and evolve platform capabilities for ML training, batch inference, and model deployment at scale
• Own and improve core platform components (compute orchestration, data pipelines, inference systems) used by multiple teams
• Enable ML engineers by building intuitive, well-documented platform tools across the model lifecycle
• Optimize hybrid compute environments (cloud + on-prem/GPU) for large-scale ML workloads using Kubernetes, Slurm, and AWS
• Provide technical guidance and mentorship to junior engineers on platform and systems design