Staff ML Engineer — Production-Grade AI Systems

ActAI

Zürich

Vor Ort

CHF 140.000 - 200.000

Vollzeit

Vor 2 Tagen
Sei unter den ersten Bewerbenden
Bewerbungsgenerator

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Zusammenfassung

ActAI in Zürich, Switzerland is hiring a Member of Technical Staff, Machine Learning to build core ML components for production systems from day one. You will ship, debug, and iterate on real-world ML under production constraints such as latency, cost, reliability, and safety.

You will work closely with senior ML engineers and product teams, develop data pipelines, training loops, and inference systems, and apply PyTorch or JAX to GPUs to improve model performance, reliability, and measurable

Qualifikationen

  • Strong foundations in machine learning and modern neural architectures.
  • Hands-on experience training, fine-tuning, or deploying ML models.
  • Comfortable writing production-quality code and learning new tools quickly.
  • Curious, coachable, and eager to learn from real systems in production.

Aufgaben

  • Build and improve ML components across data, training, evaluation, and inference.
  • Fine-tune and adapt models as part of larger production systems.
  • Implement evaluation and testing to understand model behavior.
  • Help build and maintain data pipelines for real-world and synthetic data.
  • Debug model issues, performance problems, and production incidents.
  • Ship improvements iteratively and learn from real user feedback.

Kenntnisse

Python
PyTorch
JAX
Production systems
Data pipelines
GPU computing

Tools

PyTorch
JAX
GPUs

Jobbeschreibung

ActAI in Zürich, Switzerland is hiring a Member of Technical Staff, Machine Learning to build core ML components for production systems from day one. You will ship, debug, and iterate on real-world ML under production constraints such as latency, cost, reliability, and safety.

You will work closely with senior ML engineers and product teams, develop data pipelines, training loops, and inference systems, and apply PyTorch or JAX to GPUs to improve model performance, reliability, and measurable

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