Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad PhD)

Unity South APAC (SEA, ANZ, IND Subcont.)
San Francisco, US
On-site

Why this role

Pace
Fast Paced
Collaboration
High
Autonomy
Medium
Decision Impact
Team
Role Level
Individual Contributor

What success looks like

  • build and maintain data pipelines
  • contribute to distributed training workflows
  • improve reproducibility and reliability
  • support experimentation and model iteration
Typical background
phd in computer science, machine learning, systems, or related field

Transferable backgrounds

Skills & requirements

Required

machine learningdistributed systemspythonml frameworksdata pipelinesmodel training workflowslarge datasets

Preferred

workflow orchestration systemslarge-scale data platformspublications or research in ML systems

Stack & domain

PythonPytorchRayAirflowFlyteProblem-solvingTeamworkMachine learningData processingDistributed systems

About the role

The opportunity

Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company.

Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform enables large-scale model training, feature generation, and experimentation workflows that power production ML systems.

We’re looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role…

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