Senior ML Platform Engineer

Unity

Mountain View (CA)

In loco

USD 179.000 - 232.000

Tempo pieno

2 giorni fa
Candidati tra i primi
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Vantaggi offerti da questo lavoro

Health insurance
Commuter subsidy
Equity/stock ownership
Retirement plan
Generous vacation days
Parental leave support

Descrizione del lavoro

Unity is seeking a Machine Learning Engineer to help build the platform behind our product intelligence, production ML models, and the teams that develop them. You will work across data and feature pipelines, distributed training, and model serving at scale, shaping the ML infrastructure that powers Unity's products.

The role emphasizes end-to-end ownership, cross-team collaboration, and learning new tools as priorities shift, with opportunities to impact reliability and scalability across the

Competenze

  • Experience building ML infrastructure or data platforms in production.
  • Strong Python skills and experience with data-intensive workloads.
  • Hands-on experience with ML frameworks (e.g., PyTorch) and distributed compute (e.g., Ray, Spark).

Mansioni

  • Build and maintain data and feature pipelines that generate training datasets for ML models and experimentation.
  • Develop infrastructure for distributed training workflows.
  • Operate multi-stage ML pipelines using workflow orchestration tools.
  • Contribute to model serving and deployment infrastructure to move models from training to production.

Conoscenze

Python
Communication

Formazione

Bachelor's degree in CS/ML/Systems or equivalent

Strumenti

PyTorch
Ray
Spark

Descrizione del lavoro

Unity is seeking a Machine Learning Engineer to help build the platform behind our product intelligence, production ML models, and the teams that develop them. You will work across data and feature pipelines, distributed training, and model serving at scale, shaping the ML infrastructure that powers Unity's products.

The role emphasizes end-to-end ownership, cross-team collaboration, and learning new tools as priorities shift, with opportunities to impact reliability and scalability across the

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