Senior ML/DL Developer
Stay22
-English to follow-
Chez Stay22, nous révolutionnons la façon dont les utilisateurs convertissent en ligne. Notre plateforme d’affiliation propulsée par l’IA aide les éditeurs, les plateformes de billetterie et les créateurs de contenu à générer de nouvelles sources de revenus tout en améliorant l’expérience de leur audience.
Sommaire du poste
Vous vous joindrez à la Neuro Squad , une équipe spécialisée créée pour centraliser l’innovation en ML et en IA chez Stay22. Neuro fournit les fondations techniques qui alimentent nos moteurs principaux, notamment Roam (notre moteur de redirection basé sur le machine learning) et Spark (notre moteur de logique d’affiliation propulsé par l’IA).
À titre de Développeur·se senior ML/DL au sein de la Neuro Squad, vous serez responsable de concevoir et d’architecturer l’intelligence derrière ces produits. Ce rôle ne consiste pas uniquement à créer des modèles : il s’agit de prendre en charge l’ensemble du cycle de vie de nos plateformes ML — de la conception des pipelines d’entraînement à l’optimisation des API d’inférence en temps réel.
Vous travaillerez avec des technologies de pointe (incluant les LLMs) et collaborerez étroitement avec l’équipe Données et la Forge Squad afin d’assurer que nos solutions d’IA soient évolutives, sécuritaires et prêtes pour la production.
Responsabilités principales
Machine learning et logique produit
Assumer la responsabilité de la logique backend et du comportement des modèles pour Roam et Spark, en assurant une grande précision et fiabilité.
Améliorer continuellement les modèles en matière de qualité de classement, de latence et d’efficacité des revenus à l’aide d’analyses statistiques avancées et de deep learning.
Développer des modèles haute performance pour la prévision et la prédiction de l’intention utilisateur à partir de données tabulaires complexes et de données de réservation.
Infrastructure IA et MLOps
Concevoir et maintenir le client interne LLM ainsi que les couches de passerelle, permettant un accès unifié aux modèles de langage pour l’ensemble de l’organisation.
Concevoir et opérer le cycle de vie complet du ML : préparation des données, pipelines d’entraînement, registres de modèles et services d’inférence en temps réel.
Gérer les couches de cache, les serveurs d’inférence et la surveillance des performances afin d’assurer une faible latence pour nos moteurs à fort volume de trafic.
Déployer des solutions robustes, faciles à maintenir et prêtes pour la production, alignées avec les standards CI/CD et de sécurité (en collaboration avec la Forge Squad).
Collaboration et accompagnement
Collaborer avec la Data Squad afin de co-concevoir les jeux de données d’entraînement et les pipelines de variables, en assurant une intégration fluide avec l’entrepôt de données et les systèmes analytiques.
Exposer les capacités ML sous forme d’API et de services robustes, permettant aux squads alignées (ex. Hub, EmbedX) de les intégrer facilement sans gérer la complexité ML.
Agir à titre de mentor·e et de conseiller·ère technique en soutenant les équipes dans le prototypage de fonctionnalités ML et l’adoption des meilleures pratiques en IA.
Exigences
Formation et expérience
Maîtrise de l’anglais requise pour les communications quotidiennes avec des collègues et partenaires internationaux.
Maîtrise (M. Sc.) en informatique, apprentissage automatique, fouille de données, statistiques ou domaine technique connexe.
6 ans et plus d’expérience en machine learning ou en science des données.
Minimum de 2 ans d’expérience en ingénierie logicielle, incluant l’écriture de code backend ou d’API prêts pour la production.
Machine learning et deep learning
Excellente maîtrise de Python et des bibliothèques de deep learning telles que PyTorch ou TensorFlow, ainsi que scikit-learn.
Solide compréhension des techniques ML modernes, incluant les CNN, LSTM/RNN et les modèles de gradient boosting (XGBoost, LightGBM) appliqués aux données tabulaires.
Capacité démontrée à implémenter et optimiser des LLMs, incluant les Transformers, les embeddings personnalisés et la création de passerelles ou clients LLM.
MLOps et systèmes temps réel
Expérience avec Google Vertex AI (préféré) ou Amazon SageMaker pour l’entraînement et la gestion de modèles à grande échelle.
Forte expérience dans la conception de systèmes d’inférence et d’API en temps réel (au-delà du traitement batch).
Expérience avec les outils MLOps (ex. MLflow, Kubeflow, TFX) et la conteneurisation (Docker, Kubernetes).
Excellentes compétences en SQL et expérience de collaboration sur des feature stores ou des définitions ETL.
Compétences humaines et état d’esprit
Capacité à concevoir des systèmes réutilisables, robustes et faciles à consommer pour les autres équipes.
Intérêt marqué pour la transformation de métriques ML complexes en valeur d’affaires concrète (meilleure redirection, taux de conversion plus élevé).
Désir de demeurer à l’avant-garde des infrastructures IA et des techniques de modélisation.
À quoi vous attendre dans notre processus d’embauche
Nous savons que votre temps est précieux — voici donc les grandes étapes du processus :
Appel de présélection avec notre partenaire en acquisition de talents (30 à 45 minutes)
Séance de whiteboarding sur Miro avec l’équipe d’ingénierie (60 minutes)
Entrevue en personne avec certains membres de la Neuro Squad (45 à 60 minutes)
Entrevue finale avec notre PDG (30 minutes)
Offre et intégration
Veuillez noter que ce processus peut être modifié à tout moment selon les besoins de l’équipe.
Pourquoi joindre Stay22?
Soutenir les créateurs voyage : Contribuez à une mission qui permet aux créateurs de voyager davantage grâce à l’augmentation de leurs revenus passifs.
Propulser votre croissance : Nous embauchons des personnes ambitieuses et leur offrons l’espace pour exceller, évoluer rapidement et développer leurs forces.
Avoir un impact réel : Nos équipes sont encouragées à prendre des initiatives et à influencer concrètement l’avenir de Stay22.
Emplacement de choix : Profitez de nos bureaux lumineux et dynamiques au cœur de la Petite Italie, entourés de cafés, restaurants et commerces.
Soyez vous-même : Code vestimentaire décontracté et horaire de travail flexible.
Avantages complets : Assurances santé et dentaire, régime de retraite, occasions de formation et de développement, activités sociales et retraites d’équipe.
(Stay22 est un employeur souscrivant au principe de l’égalité des chances. Toutes les candidatures qualifiées seront considérées. Si vous avez un handicap ou un besoin particulier nécessitant des mesures d’adaptation, veuillez communiquer avec nous à View email address on jobs.jobcopilot.com.)
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At Stay22, we’re revolutionizing how people convert online. Our AI-powered affiliate platform helps publishers, ticketing platforms, and content creators unlock new revenue streams while levelling up their audience's user experience. At Stay22, our partners don’t just earn more, they deliver more. Join us and be part of something big that's shaking up the affiliate world.
Job Summary
You will be joining the Neuro Squad , a specialized team formed to centralize ML/AI innovation at Stay22. Neuro provides the technical foundation that powers our core engines, including Roam (our ML-driven redirection engine) and Spark (our AI-driven affiliate logic engine).
As a Senior ML/DL Developer in the Neuro Squad, you will architect the intelligence behind these products. This role is not just about building models - it is about owning the end-to-end lifecycle of our ML platforms - from designing training pipelines to optimizing real-time inference APIs. You will leverage cutting-edge technologies (including LLMs) and collaborate with the Data Team and Forge Squad to ensure our AI solutions are scalable, secure and production-ready.
Key Responsibilities
Core ML & Product Logic
Own the backend logic and model behavior for Roam and Spark , ensuring high accuracy and reliability.
Continuously refine models for ranking quality, latency and revenue efficiency using advanced statistical analysis and deep learning.
Develop high-performance models for forecasting and user intent prediction based on complex tabular and booking data.
AI Infrastructure & MLOps
Build and maintain the internal LLM client and gateway layers , enabling unified access to language models for the entire organization.
Design and operate the full ML lifecycle: data preparation, model training pipelines, model registries and real-time inference services.
Manage caching layers, inference servers and performance monitoring to ensure low-latency responses for our high-traffic engines.
Create low-maintenance, production-ready solutions that align with CI/CD and security standards (in partnership with the Forge squad).
Collaboration & Enablement
Collaborate with the Data Squad to co-design training datasets and feature pipelines, ensuring seamless integration with the data warehouse and analytics systems.
Expose ML capabilities as robust APIs/services that stream-aligned squads (e.g. Hub, EmbedX) can easily integrate without managing the ML complexity themselves.
Act as a technical mentor and advisor, helping other teams prototype ML features and adopt AI best practices.
Requirements
Education & Experience
English proficiency is required for daily communication with international clients and colleagues.
M.S. in Computer Science, Machine Learning, Data Mining, Statistics, or a related technical field.
6+ years of total experience in Machine Learning or Data Science.
At least 2 years of specific experience in software engineering, writing production-grade code for backend services or APIs.
Core ML & Deep Learning
Proficiency in Python and deep learning libraries like PyTorch or TensorFlow, as well as scikit-learn.
Deep understanding of modern ML techniques including CNNs, LSTMs/RNNs and gradient boosting (XGBoost/LightGBM) applied to tabular data.
Proven ability to implement and fine-tune LLMs, with expertise in Transformers, custom embeddings and building LLM gateways/clients .
MLOps & Real-Time Systems
Experience with Google Vertex AI (preferred) or Amazon SageMaker for training and managing models at scale.
Strong experience building real-time inference systems and APIs (not just offline batch processing).
Experience with MLOps tools (e.g. MLflow, Kubeflow, TFX) and containerization (Docker, Kubernetes).
Strong SQL skills and experience collaborating on feature stores or ETL definitions.
Soft Skills & Mindset
Ability to design systems that are reusable, robust and easy for other teams to consume.
A passion for translating complex ML metrics into tangible business value (better routing, higher conversion).
A drive to stay ahead of the curve in AI infrastructure and modeling techniques.
What to Expect from our Hiring Process
We know your time’s valuable, so here’s the quick rundown of what to expect.
Screening call with our Talent Acquisition Partner (30-45 minutes)
Whiteboarding session oriented on Miro with the Engineering Team (60 minutes)
In person interview with some Neuro squad team members (45-60 minutes)
Final interview with our CEO (30 minutes)
Offer & onboarding
Please note that this process is subject to change at any point, based on additional requirements from the team.
Why join Stay22?
Support Travel Creators: Be part of a team that empowers travel creators to explore the world by increasing their passive income potential.
Empower Your Growth: We hire champions and give them the opportunity to excel, skipping levels and honing their superpowers.
Lead with Impact: We empower our team members to take charge and make a real impact in the Stay22 universe.
Location, Location, Location: Enjoy our bright and vibrant office in the heart of Little Italy, surrounded by great shops and restaurants
Be Yourself: Embrace a come-as-you-are dress code and a flexible work schedule.
Comprehensive Benefits: We offer health & dental benefits, retirement plans, learning & development opportunities, and social & team-building activities, including exciting retreats.
(Stay22 is an equal-opportunity employer. All qualified applicants are given consideration. If you have a disability or particular need that requires accommodation, please contact us at careers at stay22.com )
Your application will be reviewed by Mariel , our internal recruiter .
Ton CV sera lu par Mariel , notre recruteuse interne.
If you don’t meet every requirement but you’re excited, let’s talk!
Même si tu ne coches pas toutes les cases, on aimerait quand même te rencontrer !
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