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Live jobs with “Machine Learning Engineer” in the title or listed as a skill.
We are seeking a Senior Machine Learning Engineer to own the entire MLOps lifecycle, with a specific focus on LLMOps and the development of agentic systems.
Design and engineer AI-powered features for conversation intelligence. You will develop and deploy ML solutions from model pipelines to production inference. This role is remote from Spain.
Senior Machine Learning Engineer focused on designing and building scalable search, retrieval, and ranking systems for digital products.
Senior ML Engineer to design and deploy scalable AI solutions for a global financial institution. You will work on LLMs, multi-agent systems, and RAG architectures in a hybrid Madrid office.
Senior Machine Learning Engineer focused on optimizing LLM and VLM inference services. You will improve latency, throughput, and GPU utilization for frontier models. The role is remote within Europe.
Senior ML Engineer to design and deploy scalable AI solutions for a global financial institution. You will work on LLMs, multi-agent systems, and RAG architectures in an agile environment.
A Machine Learning Engineer will develop and deploy computer vision systems for hardware products. The role offers technical autonomy and access to specialized R&D laboratories.
An AI Engineer will architect and deploy robust Agentic Systems and production-grade AI agents. The role offers a professional growth environment within a technology-focused culture.
The role involves building scalable data platforms and end-to-end ML systems for R&D projects. It offers a flexible schedule and a horizontal organizational structure.
Senior Machine Learning Engineer to build and own critical ML subsystems for proactive AI products. You will design, train, and deploy reliable production systems. This is a remote, full-time role.
You will drive the development of machine learning solutions for online gaming platforms. The role offers medical insurance, open annual leave, and professional development.
The role involves reviewing and evaluating machine learning challenges to ensure they are technically sound, reproducible, and require genuine ML reasoning.
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