Machine Learning Researcher

Alexander Daniels Global; Essen; Remote; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A pioneering AI company in Essen is seeking a dedicated ML Research Engineer to enhance manufacturing efficiency through practical AI solutions. In a remote-first and collaborative setting, this role demands expertise in Bayesian Optimisation, Few-Shot Learning, and strong Python skills. The ideal candidate will engage with manufacturing customers to design effective solutions. This role offers a competitive salary, bonuses, and share options.

Leistungen

Competitive salary

Bonus

Share / equity options

Qualifikationen

• Strong understanding of optimisation under uncertainty and multi-objective optimisation.
• Expertise in Bayesian Optimisation and Gaussian Processes.
• Hands-on experience with Few-Shot Learning and statistics.

Aufgaben

• Collaborate on strategic technical decisions and develop AI solutions.
• Implement knowledge transfer capabilities across machines.

Jobbeschreibung

Overview

Our client is a pioneering AI company dedicated to transforming manufacturing processes through a “small data” approach to AI. In this role, you will be the first dedicated ML Research Engineer, responsible for building core AI capabilities that will directly impact manufacturing efficiency and sustainability at scale. You’ll work in a remote-first, collaborative environment, pioneering practical AI solutions that put an expert operator next to each industrial machine.

Responsibilities

• Collaborate on strategic technical decisions, rapidly prototype and iterate on AI solutions, and develop and implement Bayesian Optimisation algorithms that suggest batches of experiments.
• Implement knowledge transfer capabilities across machines and create robust data quality systems.

Qualifications & Requirements

• Strong understanding of optimisation under uncertainty and multi-objective optimisation, with experience engaging with manufacturing customers to understand real-world constraints.
• Expertise in Bayesian Optimisation and Gaussian Processes (theory and practical application).
• Hands-on experience with Few-Shot Learning, and a solid background in statistics and experimental design.
• Advanced proficiency in Python and libraries such as sklearn and GPflow.
• Manufacturing background and a startup mindset that prioritises practical, deployable solutions over theoretical approaches.
• Motivation to solve real-world problems with tangible industrial impact; comfortable with ambiguity and rapid priority changes.

Benefits & Work Arrangement

• Remote role
• Competitive salary
• Bonus
• Share / equity options