Staff ML Engineer — Production ML Systems

ActAI; España; Presencial; EUR 70.000 - 110.000; Jornada completa

Descripción de la vacante

ActAI is seeking a Member of Technical Staff, Machine Learning to build core ML components for production systems. You will contribute from day one, shipping reliable code, debugging issues, and iterating based on real user feedback.

The role focuses on data, training, evaluation, and inference pipelines, using Python, PyTorch, and JAX on GPUs in a fast-paced environment. Collaboration with senior engineers and product teams is expected.

Formación

• Strong foundations in ML and modern neural architectures.
• Hands-on experience training, fine-tuning, or deploying ML models.
• Able to write production-quality code and learn new tools quickly.
• Curious, coachable, and eager to learn from real systems in production.
• Able to work through ambiguity with guidance and grow ownership over time.
• Bias toward shipping, iteration, and continuous improvement.

Responsabilidades

• 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.
• Work closely with senior ML engineers and product teams.
• Work under real production constraints: latency, cost, reliability, and safety

Conocimientos

Python

Machine Learning

Debugging & iteration

Ambiguity handling

Herramientas

PyTorch

JAX

Git

Descripción del empleo

ActAI is seeking a Member of Technical Staff, Machine Learning to build core ML components for production systems. You will contribute from day one, shipping reliable code, debugging issues, and iterating based on real user feedback.

The role focuses on data, training, evaluation, and inference pipelines, using Python, PyTorch, and JAX on GPUs in a fast-paced environment. Collaboration with senior engineers and product teams is expected.