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Machine Learning Engineer

Machine Learning Engineer

Explore Group, , Spain, España
Hace 3 días
Descripción del trabajo

Overview

We’re hiring Senior ML Engineers to join a confidential, enterprise‑grade AI programme focused on automation and decision support for large‑scale business systems. The work ranges from building proof of concept GenAI applications to productionising model‑driven solutions used across large multi national customers. This is a remote‑first role for candidates based in Europe, with required overlap of US working hours (2–6 PM CET).

Responsibilities

  • Design, train and scale transformer based models for text and image tasks.
  • Own the full model lifecycle, data preparation, architecture, training, validation, deployment and ongoing monitoring.
  • Collaborate closely with data scientists, software engineers and domain specialists to turn POCs into production services.
  • Build and maintain retrieval augmented and agentic GenAI workflows.
  • Apply Deep Learning and Reinforcement Learning methods to real world enterprise problems.
  • Mentor junior engineers and help define best practices for MLOps and DataOps.

Must have experience & skills

  • Strong hands on experience with large scale Neural Networks, Deep Learning and Reinforcement Learning in production settings.
  • Practical GenAI experience, RAG style applications, vector DBs and agentic frameworks.
  • Advanced Python and core ML libraries, PyTorch, TensorFlow, SciPy, Scikit learn.
  • Solid experience with cloud platforms, Azure preferred, also AWS, GCP.
  • Proven understanding of the full ML lifecycle and MLOps tooling.
  • Experience with Probabilistic Graphical Models, Bayesian Networks, Markov Random Fields, is required.
  • Excellent problem solving, communication and collaboration skills.
  • Able to work overlapping hours with US teams, 2–6 PM CET.
  • Nice to haves

  • Track record converting POCs to scalable production systems.
  • Experience with LangChain, LlamaIndex or similar orchestration frameworks.
  • Familiarity with compliance or regulated data contexts.
  • Logistics

  • Start, ASAP
  • Location, Remote
  • Onsite, workshop attendance, 2x per year.
  • Time overlap, Required, 2–6 PM CET.
  • #J-18808-Ljbffr

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