Senior ML Platform Engineer: Scale & Serve Models

LE130 Unity Technologies SF; Mountain View (CA); In loco; USD 141.000 - 232.000; Tempo pieno

Vantaggi offerti da questo lavoro

Comprehensive health coverage

Employee stock ownership

Generous vacation and personal days

Commute subsidy

Retirement plans

Descrizione del lavoro

Unity Technologies SF is seeking a Machine Learning Engineer for its ML Engineering Infrastructure team. You will build the platform powering ML across the company, from data pipelines to distributed training and model serving.

You will work across the full ML stack and deliver end-to-end projects with initiative and collaboration. The role emphasizes strong Python expertise, production ML experience, and learning new tools quickly.

Competenze

• Experience building ML infrastructure, data platforms, or distributed systems in production.
• Strong Python skills and data-intensive workloads.
• Hands-on experience with ML frameworks (e.g., PyTorch) and distributed compute (Ray, Spark).
• Experience with data pipelines, model training workflows, or large datasets beyond academic settings.

Mansioni

• Build and maintain data and feature pipelines that generate training datasets for ML models and experimentation.
• Develop and improve infrastructure for distributed training workflows.
• Build and operate multi-stage ML pipelines using workflow orchestration tools (Airflow, Prefect).
• Contribute to model serving and deployment infrastructure for moving models from training to production.
• Improve reproducibility and reliability across the stack via monitoring, dataset validation, and testing.
• Tackle end-to-end projects from design to rollout with sound judgment.

Conoscenze

Python

ML infrastructure

Distributed systems

Data pipelines

Communication

Self-learning

Formazione

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

Strumenti

PyTorch

Ray

Spark

Kubernetes

Airflow/Prefect

Triton/KServe/Ray Serve

Prometheus/Grafana

Descrizione del lavoro

Unity Technologies SF is seeking a Machine Learning Engineer for its ML Engineering Infrastructure team. You will build the platform powering ML across the company, from data pipelines to distributed training and model serving.

You will work across the full ML stack and deliver end-to-end projects with initiative and collaboration. The role emphasizes strong Python expertise, production ML experience, and learning new tools quickly.