Lead Platform & Software Engineer — Data & AI Systems

Nicolas Cellier

I take R&D products from prototype to production across the full stack: architecture, applications, data pipelines, Kubernetes/GitOps and operations.

Trained as a research engineer, I progressively expanded from modeling and Data Science into software engineering, production platforms and technical architecture. At MotionSign, I now lead a cross-functional scope spanning business applications, data, automation, infrastructure and operations.

Professional Experience

Lead Platform & Software Engineer — R&D Systems

Société MotionSign (38)
2026-Today

Cross-functional technical lead for MotionSign’s internal systems and R&D tools, spanning infrastructure, applications and data pipelines.

  • Designed, operated and evolved internal and cloud Kubernetes platforms managed through GitOps with FluxCD.
  • Operated data services including PostgreSQL, CloudNativePG, object and persistent storage, backups and restore procedures.
  • Developed and maintained business applications in Python, TypeScript/SvelteKit and Rust/Tauri.
  • Designed and hardened ingestion, synchronization, video-processing, animation and inference pipelines.
  • Managed technical access, application identity, private networking, DNS, TLS and OAuth/OIDC integrations.
  • Turned R&D prototypes into observable, deployable, migratable and production-ready solutions.
  • Diagnosed incidents across the full chain: application, database, storage, networking and infrastructure.
  • Made architecture decisions based on robustness, simplicity, cost and delivery timelines.

Data Scientist, R&D Team

Société IVèS (38)
2024-2026
  • Managed statistical-analysis needs: infrastructure, ETL pipeline development and automation, BI dashboards, and a decision-support tool for sizing and operating an accessible telephone platform for deaf and hard-of-hearing users.
  • Explored and prototyped Data Science solutions for R&D work alongside production tools.
  • Research Engineer dedicated to the ACDC project: improving call center scheduling for deaf and hard of hearing populations
  • Data collection, time series prediction, discrete event simulation, scheduling

Postdoctoral Researcher

LAMA / LOCIE Laboratories, USMB (73)
2018-2021
  • Development of models and numerical resolution tools for two parallel projects:
  • ANR FRAISE: Heat and mass transfer through a falling film.
  • European OPTIWIND Project: Simulation of flow and icing of droplets on aircraft windshields
Recent work

R&D system industrialization

Turned a processing prototype into a deployable, observable and maintainable workflow.

Internal and cloud GitOps platform

Operated and evolved Kubernetes environments consistently, from data services to applications.

Video data pipelines

Automated synchronization, processing and artifact flows between storage and inference services.

Education
Freelance Projects

Assistance developing parametric EnergyPlus code

2025
CAELI Energie

Consolidation and optimization of a scientific library

2023
LOCIE
Publications
Machine learning-based agent staffing under uncertainty: The case of a relay call center
10.1016/j.eswa.2025.127385
Samer Alsamadi ,  Cléa Martinez ,  Canan Pehlivan ,  Nicolas Cellier ,  Oualid Jouini ,  Yiping Fang ,  Benjamin Legros ,  Franck Fontanili  
Expert Systems with Applications
2025
A simulation based digital twin approach to assessing the organization of response to emergency calls
10.1038/s41746-024-01392-2
Yann Penverre ,  Clea Martinez ,  Nicolas Cellier ,  Canan Pehlivan ,  Joel Jenvrin ,  Dominique Savary ,  Valerie Debierre ,  Florence Deciron ,  Anis Bichri ,  Quentin Lebastard ,  Emmanuel Montassier ,  Brice Leclere ,  Franck Fontanili  
npj Digital Medicine
2024
A systematic approach to classify and characterize genomic islands driven by conjugative mobility using protein signatures
10.1093/nar/gkad644
Audrey Bioteau ,  Nicolas Cellier ,  Frédérique White ,  Pierre-Étienne Jacques ,  Vincent Burrus  
Nucleic Acids Research
2023
scikit-finite-diff, a new tool for PDE solving
10.21105/joss.01356
Nicolas Cellier ,  Christian Ruyer-Quil  
Journal of Open Source Software
2019
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