Machine Learning Researcher

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

Zusammenfassung

A pioneering AI company is seeking a dedicated ML Research Engineer to enhance manufacturing efficiency through innovative AI solutions. This remote role emphasizes practical, deployable outcomes, requiring expertise in Bayesian Optimisation and a solid background in statistics. Competitive salary, bonus, and equity options are offered.

Leistungen

Competitive salary

Bonus

Share / equity options

Qualifikationen

• Strong understanding of optimisation under uncertainty and multi-objective optimisation.
• Hands-on experience with Bayesian Optimisation and Gaussian Processes.
• Advanced proficiency in Python and relevant libraries.

Aufgaben

• Collaborate on strategic technical decisions and rapidly prototype AI solutions.
• Implement knowledge transfer capabilities across machines.
• Create robust data quality systems.

Kenntnisse

Optimisation under uncertainty

Bayesian Optimisation

Gaussian Processes

Few-Shot Learning

Python proficiency

Tools

sklearn

GPflow

Jobbeschreibung

Overview

POSITION SNAPSHOT : 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 prototyping and iterating on AI solutions, and developing and implementing Bayesian Optimisation algorithms that suggest batches of experiments.
• Implement knowledge transfer capabilities across machines and create robust data quality systems.

Qualifications

• Strong understanding of optimisation under uncertainty and multi-objective optimisation, and occasional engagement with manufacturing customers to understand real-world constraints.
• Expertise in Bayesian Optimisation and Gaussian Processes (theory and practical), hands-on experience with Few-Shot Learning, and a solid background in statistics and experimental design.
• Advanced proficiency in Python and libraries like sklearn and GPflow.
• Manufacturing background and a startup mindset that prioritises practical, deployable solutions over theoretical approaches.

Role Details

• Remote role, competitive salary, Bonus, Share / equity options.

Position Snapshot is a summary of the role. Full job description is available from the client