Machine Learning Engineer

Description

Offer Description: The position will be in the framework of the ERC Starting Grant DYNASTY (Dynamics-Aware Theory of Deep Learning). The position might include traveling to conferences for paper presentation. Travel expenses will be covered within the limits of the scale in force. We are seeking a Machine Learning Engineer to design and develop a Python software library for evaluating theoretical generalization bounds in deep learning. The objective is to bridge the gap between theoretical advances in learning theory and practical deep learning by providing a modular, efficient, and user-friendly framework for computing and comparing generalization bounds on modern neural networks. Conduct experiments for empirical verification Prepare software libraries Write scientific articles Disseminate the scientific work in appropriate venues. Requirements: Skills/Qualifications Strong Python programming skills and experience with PyTorch. Solid understanding of machine learning and deep learning. Experience in scientific software development, testing, and version control. Familiarity with statistical learning theory and generalization bounds is a plus. Ability to work collaboratively with researchers and translate mathematical concepts into reliable software. Languages FRENCH Level Basic Languages ENGLISH Level Good Additional Information: Benefits Subsidized meals Partial reimbursement of public transport costs Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.) Possibility of teleworking and flexible organization of working hours Professional equipment available (videoconferencing, loan of computer equipment, etc.) Social, cultural and sports events and activities Access to vocational training Social security coverage Selection process Website for additional job details https://jobs.inria.fr/public/classic/en/offres/2026-10601 Bando dell'ente: Machine Learning Engineer Download job offer in PDF format Contract type : Fixed-term contract Level of qualifications required : Graduate degree or equivalent Fonction : Temporary scientific engineer Level of experience : Recently graduated Context The position will be in the framework of the ERC Starting Grant DYNASTY (Dynamics-Aware Theory of Deep Learning). The position might include traveling to conferences for paper presentation. Travel expenses will be covered within the limits of the scale in force. Assignment We are seeking a Machine Learning Engineer to design and develop a Python software library for evaluating theoretical generalization bounds in deep learning. The objective is to bridge the gap between theoretical advances in learning theory and practical deep learning by providing a modular, efficient, and user-friendly framework for computing and comparing generalization bounds on modern neural networks. Main activities Conduct experiments for empirical verification Prepare software libraries Write scientific articles Disseminate the scientific work in appropriate venues. Skills Strong Python programming skills and experience with PyTorch. Solid understanding of machine learning and deep learning. Experience in scientific software development, testing, and version control. Familiarity with statistical learning theory and generalization bounds is a plus. Ability to work collaboratively with researchers and translate mathematical concepts into reliable software. Benefits package Subsidized meals Partial reimbursement of public transport costs Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.) Possibility of teleworking and flexible organization of working hours Professional equipment available (videoconferencing, loan of computer equipment, etc.) Social, cultural and sports events and activities Access to vocational training Social security coverage Apply for this position Share Facebook Linkedin Twitter Email General Information Theme/Domain : Optimization, machine learning and statistical methods Software engineering (BAP E) Town/city : Paris Inria Center : Centre Inria de Paris Starting date : 2026-12-01 Duration of contract : 2 years Deadline to apply : 2026-11-13 Warning : you must enter your e-mail address in order to save your application to Inria. Applications must be submitted online on the Inria website. Processing

Sectors

Source

Source: euraxess.ec.europa.eu