Applied ML Engineer — Build Production-Ready ML

Jobgether SRL; España; Presencial; EUR 70.000 - 110.000; Jornada completa

Descripción de la vacante

Partner company in Spain seeks an Applied ML Engineer to bridge research and production, focusing on evaluation, tooling, and user-facing insights. You will turn research ideas into rigorously tested experiments and robust production features.

Expect collaboration across research, engineering, and product, with emphasis on ownership, reproducibility, and delivering trustworthy ML systems in a fast-moving startup environment.

Formación

• Strong Python engineering with ML background.
• Experience with PyTorch and Hugging Face Transformers.
• Ability to read ML research and implement methods from first principles.
• Professional software engineering experience beyond notebooks, including APIs, asynchronous jobs, databases, logging, testing, deployment, and documentation.

Responsabilidades

• Reproduce and evaluate ML research methods using open-weight models.
• Design evaluation datasets, probes, scoring approaches, baselines, calibration tests, and experiment harnesses.
• Work with model weights, logits, hidden states, activations, model APIs, and inference infrastructure.
• Build and extend evaluation infrastructure covering experiment runners, judges, persistence, orchestration, reporting, and reproducibility.
• Turn research workflows into intuitive product experiences, including experiment configuration, execution, traces, comparisons, reports, and review workflows.
• Investigate how verification methods behave when models are modified through fine-tuning, merging, quantization, distillation, safety removal, or deliberate evasion.

Conocimientos

Python

Communication

Analytical thinking

ML research literacy

Herramientas

PyTorch

Hugging Face Transformers

DSPy

LiteLLM

Temporal

Ray

vLLM

PostgreSQL/pgvector

Next.js

React

TypeScript

Descripción del empleo

Partner company in Spain seeks an Applied ML Engineer to bridge research and production, focusing on evaluation, tooling, and user-facing insights. You will turn research ideas into rigorously tested experiments and robust production features.

Expect collaboration across research, engineering, and product, with emphasis on ownership, reproducibility, and delivering trustworthy ML systems in a fast-moving startup environment.