The role

We are seeking a highly skilled and customer-focused professional to join our team as a Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.

You’re welcome to work from France or any country in the Iberian Peninsula (Spain, Portugal, or Andorra).

Your responsibilities will include: 

• Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices.
• Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers.
• Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI.
• Act as a single point of expertise of customer scenarios for product, technical support, marketing teams.
• Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)

We expect you to have: 

• 5+ years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing
• Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python
• Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL)
• Excellent communication skills, fluency in French or Spanish preferred
• Customer-centric mindset

It will be an added bonus if you have: 

• Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow)
• Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch)
• Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google) 

The role

At Nebius, we’re building a next-generation AI compute platform for large-scale ML training and inference — from a few nodes to thousands of GPUs.
We’re looking for a Technical Product Manager to own product direction for Soperator — our Slurm-on-Kubernetes control plane for GPU clusters.
In this role, you will shape how ML engineers and research teams run, scale, and optimize distributed workloads in production.
If you care about systems that combine performance, reliability, and developer experience at the frontier of AI infrastructure, this role is for you.

Your responsibilities will include: 

• Own the full user journey across Soperator clusters: Slurm workflows, dashboards, alerts/notifications, node lifecycle, and training/inference capacity management.
• Define product direction end-to-end: problem discovery → solution design → delivery → adoption.
• Lead deep customer discovery through interviews, usage analytics, and workload analysis to uncover high-impact opportunities.
• Drive execution across platform teams: compute, networking, storage, observability, IAM and etc.
• Translate frontier ML and infrastructure ideas into practical product capabilities for real-world GPU clusters.
• Define success metrics, prioritize roadmap decisions with data, and ensure measurable customer/business impact.
• Lead the open-source strategy and execution for Soperator: shape public roadmap themes, prioritize OSS-facing capabilities, and ensure strong adoption in the community.  

We expect you to have: 

• 3–5+ years in Product Management, ML infrastructure/MLOps, distributed systems, or cloud platform engineering.
• Strong technical depth in distributed systems, cloud infrastructure, or ML platforms.
• Hands-on familiarity with large-scale ML training and orchestration tools (e.g., Slurm, Kubernetes, Ray).
• Track record of shipping technically complex products with multiple engineering teams.
• Strong communication and stakeholder management across engineering, research, and customers.
• Experience with product analytics, data-informed prioritization, and experimentation.
• High ownership, high learning velocity, and comfort operating in fast-moving AI infrastructure environments.

It will be an added bonus if you have: 

• Experience with GPU platforms and HPC primitives: InfiniBand/RDMA, topology-aware scheduling, high-throughput storage.
• Practical understanding of modern ML training stacks: PyTorch, DeepSpeed, FSDP/ZeRO, NCCL.
• Familiarity with efficiency and reliability metrics: Goodput, MFU, failure modes, preemption handling, health checks.
• Exposure to large-scale LLM training/inference systems.
• Experience in observability, performance tuning, or SRE/reliability engineering.
• Customer-facing technical experience (solutioning, support, architecture advisory).

About Nebius

Nebius AI is an AI cloud platform with one of the largest GPU capacities in Europe. Launched in November 2023, the Nebius AI platform provides high-end, training-optimized infrastructure for AI practitioners. As an NVIDIA preferred cloud service provider, Nebius AI offers a variety of NVIDIA GPUs for training and inference, as well as a set of tools for efficient multi-node training. 

Nebius AI owns a data center in Finland, built from the ground up by the company’s R&D team and showcasing our commitment to sustainability. The data center is home to ISEG, the most powerful commercially available supercomputer in Europe and the 16th most powerful globally (Top 500 list, November 2023).  

Nebius’s headquarters are in Amsterdam, Netherlands, with teams working out of R&D hubs across Europe and the Middle East. 

Nebius AI is built with the talent of more than 500 highly skilled engineers with a proven track record in developing sophisticated cloud and ML solutions and designing cutting-edge hardware. This allows all the layers of the Nebius AI cloud – from hardware to UI – to be built in-house, distictly differentiating Nebius AI from the majority of specialized clouds: Nebius customers get a true hyperscaler-cloud experience tailored for AI practitioners. We’re growing and expanding our products every day. 

The role

We seek an experienced Specialist Solutions Architect to support AI-focused customers leveraging Nebius services. In this role, you will be a trusted advisor, collaborating with clients to design scalable AI solutions, resolve technical challenges and manage large-scale AI deployments involving hundreds to thousands of GPUs.

You’re welcome to work on-site in Amsterdam or remotely from any other EU country.

Your responsibilities will include:

• Designing customer-centric solutions that maximize business value and align with strategic goals.
• Building and maintaining long-term relationships to foster trust and ensure customer satisfaction.
• Delivering technical presentations, producing whitepapers, creating manuals and hosting webinars for audiences with varying technical expertise.
• Collaborating with engineering and product teams to effectively prioritize and relay customer feedback.

We expect you to have:

• 3+ years of experience with cloud technologies in MLOps engineering, Machine Learning engineering or similar roles.
• Strong understanding of ML ecosystems, including models, use cases and tooling.
• Proven experience in setting up and optimizing distributed training pipelines across multi-node and multi-GPU environments.
• Hands-on knowledge of frameworks like PyTorch or JAX.
• Excellent verbal and written communication skills.

It will be an added bonus if you have:

• Expertise in deploying inference infrastructure for production workloads.
• Ability to transition ML pipelines from POC to scalable production systems.

Preferred tooling:

• Programming Languages – Python, Go, Java, C++
• Orchestration – Kubernetes (K8s), Slurm
• DevOps Tools – Git, Docker, Helm
• Infrastructure as Code (IaC) – Terraform
• ML Frameworks and Libraries – PyTorch, TensorFlow, JAX, HuggingFace, Scikit-learn

Customer experience

Customer experience at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions.

Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.

The role

We are looking for a Partner Solutions Architect to serve as the technical interface between Nebius and our strategic technology partners, ranging from data platforms and MLOps vendors to AI frameworks and ISVs that build on GPU infrastructure. 

This is a hands-on engineering and integration role. You will design and develop integrated solutions, build reference implementations, enable partner engineering teams, and ensure joint customers succeed with combined offerings. You will influence Nebius’ product roadmap and drive deep technical collaboration across partner ecosystems.

You’re welcome to work from our office in Amsterdam or remotely from any EU country.

Your responsibilities will include: 

• Own the technical relationship with strategic partners as the primary interface to Nebius engineering and product
• Design and architect high-impact integration solutions, delivering clear joint customer value
• Build and maintain reference implementations and production-grade integrations
• Define enterprise-ready integration patterns (networking, security, compliance, observability)
• Translate partner and customer feedback into actionable product and roadmap requirements
• Enable partner teams through technical documentation, training, and demo environments
• Provide technical leadership in joint customer deployments, architecture reviews, and complex troubleshooting

We expect you to have: 

• 5+ years in solutions architecture, partner engineering, or technical pre-sales at cloud or data platform companies
• Strong expertise in cloud infrastructure
• Hands-on experience with GPU-accelerated AI/ML workflows (training, inference, MLOps)
• Proven background in integration architecture (API design, data pipelines, security, observability)
• Experience with Python and IaC tools
• Excellent communication skills with the ability to engage technical and non-technical stakeholders

It will be an added bonus if you have: 

• Track record of building or scaling partner technical programs or ecosystems
• Experience working with or at Snowflake, Databricks, AWS, Azure, or GCP
• Background in ML lifecycle (training pipelines, fine-tuning, inference optimization, RAG

The role

We are seeking a customer-obsessed Solutions Architect to lead technical engagement with Nebius customers across Europe. This role is focused on presales excellence, strong technical storytelling, and driving adoption of Nebius AI Cloud across a wide range of industry segments.

As a Solutions Architect, you will act as a trusted technical partner to customers, helping them understand, evaluate, and adopt Nebius for their AI/ML and high-performance computing workloads. You will combine deep technical expertise with strong communication skills to clearly articulate Nebius’ value proposition and differentiate our platform in a competitive market.

You’re welcome to work remotely from Europe.

Your responsibilities will include:

• Own end-to-end technical presales engagements, from discovery through solution design, PoC execution, and production readiness
• Serve as a trusted technical advisor to customer stakeholders, including CTOs, Heads of AI/ML, and platform engineering teams
• Deliver compelling technical presentations, demos, and workshops that clearly communicate the value of Nebius across different customer segments
• Execute demos and PoCs to demonstrate performance, scalability, and cost efficiency of Nebius solutions
• Translate customer requirements into scalable, production-ready architectures and best practices
• Collaborate closely with Sales, Product, and Engineering to align customer needs with Nebius capabilities and roadmap
• Act as a technical advocate for customers internally, ensuring feedback is incorporated into product and go-to-market strategy
• Support regional go-to-market efforts, including events, meetups, webinars, and technical content creation
• Contribute to building repeatable technical playbooks and assets for the European market

We expect you to have:

• 2–5+ years of experience in technical roles such as Solutions Architect, Cloud Architect, Sales Engineer, or similar, with strong customer-facing exposure
• Proven experience in presales or customer-facing technical roles, including discovery, solution design, and PoC execution
• Strong ability to deliver technical pitches and clearly explain complex infrastructure and AI/ML concepts to both technical and business audiences
• Experience positioning cloud or infrastructure solutions and articulating value propositions in competitive environments
• Solid understanding of ML/AI workloads, including training and inference, and the underlying infrastructure requirements
• Experience with cloud platforms, Kubernetes, and distributed systems
• Hands-on experience with Infrastructure as Code (e.g., Terraform) and scripting/programming (Python preferred)
• Strong communication and storytelling skills, with the ability to adapt messaging across different customer segments
• Deep understanding of the European market, including customer expectations, buying behaviors, and local ecosystem
• Fluency in English plus another language preferred (both written and spoken), with the ability to engage confidently with local customers and stakeholders
• A highly customer-centric mindset, with the ability to balance technical depth and business value

It will be an added bonus if you have:

• Experience with GPU-accelerated workloads and AI infrastructure (NVIDIA ecosystem, CUDA, etc.)
• Hands-on experience with MLOps tools and frameworks (Kubeflow, MLflow, etc.)
• Familiarity with HPC environments and schedulers (e.g., Slurm)
• Experience contributing to regional go-to-market or developer/community initiatives

Role & Team

We’re looking for a Director of Platform & Infrastructure to own and evolve our core engineering foundations. Reporting to our VP of Product Engineering, this role will lead SRE, MLOps, and Platform teams with a mandate to create leverage across the entire organization.

As a scaling startup, we’re evolving from early-stage infrastructure to a more mature, reliable platform that can support rapid product development and growing customer demand. This role is critical in helping us make that transition — building systems, standards, and teams that enable speed today while laying the foundation for long-term scale.

Partnering closely with product, data, and application engineering teams, you will set the technical vision, define best practices, and ensure our infrastructure enables teams to move fast with confidence.

This is a highly cross-functional leadership role for someone who combines deep technical judgment with a systems mindset, strong people leadership, and a passion for building platforms that empower others.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do 

• Own the platform strategy across Platform, MLOps, and SRE, aligning it with company and product goals
• Grow senior ICs (and eventually manages) across multiple teams, fostering strong technical leadership and healthy team cultures
• Define and evolve our platform vision, including developer experience, internal tooling, CI/CD, infrastructure, observability, and reliability standards
• Oversee MLOps systems that support model development, training, deployment, monitoring, and governance in production
• Partner cross-functionally with Product, ML, Data, Security, and Compliance to ensure the platform meets current and future needs
• Balance speed and stability, making thoughtful tradeoffs between innovation, cost, reliability, and operational excellence
• Set metrics and accountability for platform performance, reliability, and developer productivity

Skills & Experience

• 10+ years experience leading platform, infrastructure, or reliability teams in a scaling startup environment, including navigating ambiguity, rapid growth, and the transition from early-stage systems to more mature, repeatable platforms
• Strong understanding of cloud-native infrastructure (GCP strongly preferred), Kubernetes, CI/CD, and modern DevOps practices
• Experience supporting machine learning systems in production, including model deployment, monitoring, and lifecycle management
• A track record of building reliable, scalable systems used by fast-moving product teams
• Excellent people leadership skills — you know how to coach managers, grow talent, and build inclusive, high-performing teams
• Strong communication skills and the ability to influence across org boundaries
• Experience in data- or ML-heavy products

Nice To Have

• Experience with geospatial data, image processing or mapping technology 

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits.  
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

REJOINS L'ÉQUIPE PRICE & PROMOTION RECOMMENDATION ENGINE

Au sein du domaine Customer Relationship, notre équipe développe et industrialise des solutions d'IA dédiées à la stratégie de prix de Decathlon. Nous concevons des moteurs de recommandation qui calculent le prix optimal de chaque produit en analysant l'élasticité-prix, les données de comportement d'achat des clients et les indicateurs de performance du marché.

L'objectif est d'intégrer ces modèles dans la stratégie Decathlon pour garantir une cohérence entre l'offre et les attentes des utilisateurs.

Pour cela, nous collaborons dans une organisation agile composée de Product Managers, Data Scientists, Data Engineers, Machine Learning Engineers et Data Analysts.

MACHINE LEARNING ENGINEER - ALTERNANCE

Dans le cadre de l’ouverture d’un poste en interne, nous recrutons un.e Machine Learning Engineer en contrat d’apprentissage/stage, basé.e à Paris.

Déployer les moteurs de recommandation en production est un enjeu clé pour fournir des recommandations précises, fiables et robustes. Ton rôle sera de garantir que nos modèles de prix et de promotions s'adaptent en continu aux besoins des sportifs. Tu travailleras sur l'industrialisation du cycle de vie des modèles pour assurer une expérience fluide et sans friction sur tous nos canaux (digital et magasins) via les bonnes pratiques MLOps.

Cela inclut différentes problématiques telles que le monitoring de la qualité et de l’évolution des données (data drift), la surveillance des performances du modèle, l’orchestration des prédictions, la stratégie de ré-entraînement du modèle… Une bonne maîtrise de ces sujets est essentielle pour pérenniser la valeur créée par le modèle.

TES MISSIONS

Parfaitement intégré(e) à l'équipe en place, ton rôle sera de participer à chaque étape des projets, du cadrage à la solution finale, et de découvrir les bonnes pratiques de développement. Tu contribueras à la mise à l'échelle des solutions data et d'apprentissage automatique d'un POC à un produit entièrement déployé.

Tu commenceras par une période de formation avant de travailler sur les projets de l’équipe sous la responsabilité d'un référent Data expérimenté.

• Tu contribueras aux projets existants comme tous les membres de l’équipe.
• Tu effectueras une revue de l'état de l'art scientifique sur le domaine (ex. orchestration d’agents IA).
• Tu testeras ces nouvelles méthodes sur un cas d'usage réel étudié en ce moment dans notre équipe en appliquant les meilleurs standards Data.
• Tu implémenteras ces nouvelles fonctionnalités dans nos pipelines et mettre en production ton modèle en utilisant des principes d'ingénierie de qualité.
• Tu communiqueras efficacement l'analyse et les résultats par le biais de visualisations, de documents et de présentations aux parties prenantes techniques et business.

Tu auras l’opportunité de :

• Mettre à contribution tes compétences acquises lors de ta formation pour t'adapter rapidement à la stack technique Decathlon : Python - Git - SQL - Spark - Visualisation.
• Développer et documenter tes modèles et analyses (data sourcing, hypothèses et méthodes) dans une logique Agile en respectant les standards appliqués au sein des équipes Decathlon.
• Expliquer l’utilisation de la data et sa valeur ajoutée.

TON ENVIRONNEMENT TECHNIQUE

• Data & ML : Python, Scikit-Learn, Pytorch, Pyspark, SQL
• Cloud & Infra : AWS, GCP, Databricks
• MLOps : MLFlow (tracking), Airflow (orchestration), Evidently (monitoring).
• DevOps & Tools : GitHub Actions, Git, Docker, API
• Méthodologie : Agile

CE DONT TU AS BESOIN POUR RÉUSSIR

• Une première expérience significative (projets universitaire, stage ou alternance) dans un environnement technique similaire.
• Une appétence forte pour le travail en équipe et une culture du partage.
• Un intérêt pour l’impact du sport sur le développement personnel et collectif.
• L’envie de rejoindre une entreprise engagée dans le Tech4Good et l’innovation responsable.

POURQUOI NOUS REJOINDRE ?

Chez Decathlon, nous mettons un point d’honneur à offrir un cadre de travail épanouissant et motivant.

🚀 Un environnement de travail stimulant : entreprise certifiée Great Place to Work et Happy Trainees.
💰 Des avantages attractifs (après 3 mois d’ancienneté) :

• Primes mensuelles, intéressement, actionnariat
• Avantages CSE
• 25% de réduction sur nos produits
• Prise en charge de ta CVEC
• Remboursement de 50% du titre de transport & aide à la mobilité urbaine
  🎯 Un accompagnement sur mesure : coaching, formations internes et externes, partage de connaissances.
  ⚡ Une culture du sport et du test produit : deviens ambassadeur.trice de nos innovations et rejoins nos équipes sportives internes !

FAQ – TOUTES TES QUESTIONS

Comment préparer ma candidature et comment se déroule le processus de recrutement ?

1️⃣ Lis bien l’offre et mets en avant tes expériences et compétences les plus pertinentes.
2️⃣ Personnalise ton CV pour te démarquer.
3️⃣ Après candidature, tu recevras une réponse sous quatre semaines. Si tu es sélectionné.e, tu passeras au moins deux entretiens avec ton futur leader et un.e référent.e métier.

Je ne connais pas le secteur du sport, ai-je ma place chez Decathlon ?

Bien sûr ! Nous recherchons avant tout des personnes passionnées et motivées, que ce soit dans leur domaine d’expertise ou par le sport en général.

Être étudiant chez Decathlon, c’est quoi ?

C’est bien plus qu’une simple alternance ou un stage ! C’est façonner ton avenir professionnel en contribuant à des projets concrets qui ont du sens pour toi, tout en étant accompagné et soutenu à chaque étape.

🎯 Notre ambition ? T’offrir une expérience enrichissante pour te préparer à ton futur métier et, pourquoi pas, t’accueillir en CDI à l’issue de ton alternance. D’ailleurs, plus de 50% de nos étudiants rejoignent définitivement l’aventure Decathlon ! 🚀

L’équipe Business Capability Platform recherche un·e Data Scientist / Machine Learning Engineer (f/m/d) en Alternance basé·e à Paris.

PRÉSENTATION DE L'ÉQUIPE

Rejoins une équipe dynamique d'une dizaine d'expert·es data (Data Scientist, ML Engineer, Data Analysts, Analytics Engineer) au cœur de la stratégie technologique de Decathlon.  Notre mission est de construire des plateformes scalables pour transformer l'expérience client et sécuriser nos opérations. Nous relevons des défis passionnants tels que la modération automatique d'avis et la lutte contre la fraude, avec un impact direct sur des millions d'utilisateurs·trices à travers le monde. Chez nous, l'innovation se conjugue avec l'esprit d'équipe et le droit à l'erreur pour grandir ensemble.

TA FUTURE CONTRIBUTION

En tant qu'alternant·e, tu seras pleinement intégré·e au cycle de vie de nos produits Data. 

Tes missions principales incluront :

• Conception & Développement : Participer à l'industrialisation des pipelines de données et de Machine Learning (training et inférence).

• Mise en production (MLOps) : déployer des modèles via Docker et Kubernetes et assurer l'intégration continue (CI/CD) pour garantir la stabilité de nos services.
• Optimisation : Contribuer à l'amélioration de la qualité du code (testing, refactoring) et à l'optimisation des performances algorithmiques.

• Monitoring : Mettre en place et suivre les indicateurs de performance des modèles en production (Drift detection, MLflow).

CE QUE TU APPORTES

• Tu prépares un diplôme de niveau Master (École d'Ingénieur ou Université) avec une spécialisation en Data Science ou Machine Learning.

• Tu as une première expérience (projet académique ou stage) en manipulation de données et modélisation.
• Tu es reconnu·e pour ta curiosité technique, ton esprit d'analyse et ton envie d'apprendre au sein d'un environnement technologique de pointe.

STACK TECHNIQUE

• Langages : Python (expert), SQL.
• ML/Ops : MLflow, Docker, Kubernetes, CI/CD (exemple : GitHub Actions).
• Data : Spark, Pandas, Scikit-learn, PyTorch/TensorFlow.

CE DONT TU AS BESOIN POUR RÉUSSIR

• Une première expérience significative (projets universitaire, stage ou alternance) dans un environnement technique similaire.
• Une appétence forte pour le travail en équipe et une culture du partage.
• Un intérêt pour l’impact du sport sur le développement personnel et collectif.
• L’envie de rejoindre une entreprise engagée dans le Tech4Good et l’innovation responsable.

POURQUOI NOUS REJOINDRE ?

Chez Decathlon, nous mettons un point d’honneur à offrir un cadre de travail épanouissant et motivant.

🚀 Un environnement de travail stimulant : entreprise certifiée Great Place to Work et Happy Trainees.
💰 Des avantages attractifs (après 3 mois d’ancienneté) :

• Primes mensuelles, intéressement, actionnariat
• Avantages CSE
• 25% de réduction sur nos produits
• Prise en charge de ta CVEC
• Remboursement de 50% du titre de transport & aide à la mobilité urbaine
  🎯 Un accompagnement sur mesure : coaching, formations internes et externes, partage de connaissances.
  ⚡ Une culture du sport et du test produit : deviens ambassadeur.trice de nos innovations et rejoins nos équipes sportives internes !

FAQ – TOUTES TES QUESTIONS

Comment préparer ma candidature et comment se déroule le processus de recrutement ?

1️⃣ Lis bien l’offre et mets en avant tes expériences et compétences les plus pertinentes.
2️⃣ Personnalise ton CV pour te démarquer.
3️⃣ Après candidature, tu recevras une réponse sous deux semaines. Si tu es sélectionné.e, tu passeras au moins deux entretiens avec ton futur leader et un.e référent.e métier.

Je ne connais pas le secteur du sport, ai-je ma place chez Decathlon ?

Bien sûr ! Nous recherchons avant tout des personnes passionnées et motivées, que ce soit dans leur domaine d’expertise ou par le sport en général.

Être étudiant chez Decathlon, c’est quoi ?

C’est bien plus qu’une simple alternance ou un stage ! C’est façonner ton avenir professionnel en contribuant à des projets concrets qui ont du sens pour toi, tout en étant accompagné et soutenu à chaque étape.

🎯 Notre ambition ? T’offrir une expérience enrichissante pour te préparer à ton futur métier et, pourquoi pas, t’accueillir en CDI à l’issue de ton alternance. D’ailleurs, plus de 50% de nos étudiants rejoignent définitivement l’aventure Decathlon ! 🚀

The AI Platform owns Datadog’s entire AI stack—everything from distributed training infrastructure (for our SOTA models) to the frameworks that power Bits AI, LLMObs, and the next wave of generative‑AI experiences. We’re expanding beyond model creation to the tooling that lets engineers ship production‑grade GenAI systems: retrieval‑augmented pipelines, autonomous agents, and evaluation harnesses.

We’re looking for a Senior Engineer to design and build this next‑gen platform, partner with Applied AI, product, and core‑infra teams to deliver:

• Large‑scale experimentation, training, deployment, and monitoring

• Developer toolchains for agents and other GenAI applications

• Low‑latency serving infrastructure that plugs AI features into any Datadog product

At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them.

What You’ll Do:

• Lead the design, development, and deployment of scalable tools and infrastructure to support the efforts of our data scientists (model training & serving infra, CI/CD, orchestration, deployment,...)
• Create a development ecosystem that enables rapid experimentation and deployment of algorithms 
• Stay on the cutting edge of development in the MLOps domain and document best practices to share across teams 
• Drive the technical growth of Machine Learning as a distributed capability at Datadog, spanning all product areas, as well as leverage DD’s knowledge in observability to contribute back to the MLOps community

Who You Are:

• You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or a related scientific field or equivalent experience
• You are a software engineer at heart with 5+ years of professional experience in building distributed systems, data science applications, and/or machine learning engineering
• You have proven ability to architect, build, and operate distributed systems to solve problems at a high scale
• You have extensive experience executing projects that span data engineering, data science, and machine learning
• You ship fast, route around blockers, and are comfortable working with ambiguity
• You’re happy to jump into any part of the stack and do whatever’s needed to move a project forward
• You have demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output.
• Bonus: you’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products.

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth:

• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• Intradepartmental mentor and buddy program for in-house networking
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
• Access to Inclusion Talks, our internal panel discussions
• Free, global mental health benefits for employees and dependents age 6+
• Competitive global benefits

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Hybrid

Who we are

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.

Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.

Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai.

What you will be doing - Key responsibilities

As a Senior Data Scientist, you will play a key role in designing, delivering, and scaling AI solutions for our clients. You will be responsible for ensuring technical excellence while mentoring less experienced data scientists and acting as a trusted advisor for business stakeholders.

Your main responsibilities will include:

Delivering end-to-end AI projects

• Frame use cases with business teams, validate data availability, and define the right approach.
• Design and implement machine learning or generative AI solutions that create measurable business impact.
• Ensure solutions are robust, scalable, and production-ready by applying software engineering and MLOps best practices.

Driving technical excellence

• Translate business requirements into robust AI pipelines and architectures.
• Promote best practices in coding, testing, and deployment to guarantee maintainability and scalability.
• Explore and apply advanced AI techniques to solve complex client problems.

Being a trusted advisor for clients and teams

• Explain AI approaches in clear and pragmatic terms, highlighting feasibility, risks, and ROI.
• Build strong relationships with client stakeholders, from operational teams to managers.
• Act as a go-to expert for technical guidance within projects.

Contributing to team and knowledge development

• Mentor junior data scientists, provide feedback, and support their growth.
• Share best practices through workshops, documentation, and informal training sessions.
• Contribute to internal accelerators and tools to increase delivery efficiency across projects.
• Maintain active technology watch and bring new methods, tools, and frameworks into practice.

Qualifications - What we are looking for

• 3+ years of hands-on experience developing and deploying data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience delivering AI projects in cloud environments.

In addition to technical expertise, we value individuals who can:

• Show intellectual curiosity and structured problem-solving.
• Approach challenges with pragmatism and creativity.
• Bridge the gap between business stakeholders and technical teams.Deliver with autonomy and reliability, ensuring client satisfaction.Share knowledge and mentor more junior colleagues.Build trust with clients through clear communication and rigor.

Our recruitment process

1. HR call 
2. Standard Interview 
3. Technical Interview 
4. Fit Interview

At Artefact, we recruit our employees only on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.

Who we are

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.

Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.

Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai.

What you will be doing - Key responsibilities

As a Senior Data Scientist, you will play a key role in designing, delivering, and scaling AI solutions for our clients. You will be responsible for ensuring technical excellence while mentoring less experienced data scientists and acting as a trusted advisor for business stakeholders.

Your main responsibilities will include:

Delivering end-to-end AI projects

• Frame use cases with business teams, validate data availability, and define the right approach.
• Design and implement machine learning or generative AI solutions that create measurable business impact.
• Ensure solutions are robust, scalable, and production-ready by applying software engineering and MLOps best practices.

Driving technical excellence

• Translate business requirements into robust AI pipelines and architectures.
• Promote best practices in coding, testing, and deployment to guarantee maintainability and scalability.
• Explore and apply advanced AI techniques to solve complex client problems.

Being a trusted advisor for clients and teams

• Explain AI approaches in clear and pragmatic terms, highlighting feasibility, risks, and ROI.
• Build strong relationships with client stakeholders, from operational teams to managers.
• Act as a go-to expert for technical guidance within projects.

Contributing to team and knowledge development

• Mentor junior data scientists, provide feedback, and support their growth.
• Share best practices through workshops, documentation, and informal training sessions.
• Contribute to internal accelerators and tools to increase delivery efficiency across projects.
• Maintain active technology watch and bring new methods, tools, and frameworks into practice.

Qualifications - What we are looking for

• 3+ years of hands-on experience developing and deploying data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience delivering AI projects in cloud environments.

In addition to technical expertise, we value individuals who can:

• Show intellectual curiosity and structured problem-solving.
• Approach challenges with pragmatism and creativity.
• Bridge the gap between business stakeholders and technical teams.Deliver with autonomy and reliability, ensuring client satisfaction.Share knowledge and mentor more junior colleagues.Build trust with clients through clear communication and rigor.

Our recruitment process

1. HR call 
2. Standard Interview 
3. Technical Interview 
4. Fit Interview

At Artefact, we recruit our employees only on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.

Who we are

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.

Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.

Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai.

What you will be doing - Key responsibilities

As a Senior Data Scientist, you will play a key role in designing, delivering, and scaling AI solutions for our clients. You will be responsible for ensuring technical excellence while mentoring less experienced data scientists and acting as a trusted advisor for business stakeholders.

Your main responsibilities will include:

Delivering end-to-end AI projects

• Frame use cases with business teams, validate data availability, and define the right approach.
• Design and implement machine learning or generative AI solutions that create measurable business impact.
• Ensure solutions are robust, scalable, and production-ready by applying software engineering and MLOps best practices.

Driving technical excellence

• Translate business requirements into robust AI pipelines and architectures.
• Promote best practices in coding, testing, and deployment to guarantee maintainability and scalability.
• Explore and apply advanced AI techniques to solve complex client problems.

Being a trusted advisor for clients and teams

• Explain AI approaches in clear and pragmatic terms, highlighting feasibility, risks, and ROI.
• Build strong relationships with client stakeholders, from operational teams to managers.
• Act as a go-to expert for technical guidance within projects.

Contributing to team and knowledge development

• Mentor junior data scientists, provide feedback, and support their growth.
• Share best practices through workshops, documentation, and informal training sessions.
• Contribute to internal accelerators and tools to increase delivery efficiency across projects.
• Maintain active technology watch and bring new methods, tools, and frameworks into practice.

Qualifications - What we are looking for

• 3+ years of hands-on experience developing and deploying data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience delivering AI projects in cloud environments.

In addition to technical expertise, we value individuals who can:

• Show intellectual curiosity and structured problem-solving.
• Approach challenges with pragmatism and creativity.
• Bridge the gap between business stakeholders and technical teams.Deliver with autonomy and reliability, ensuring client satisfaction.Share knowledge and mentor more junior colleagues.Build trust with clients through clear communication and rigor.

Our recruitment process

1. HR call 
2. Standard Interview 
3. Technical Interview 
4. Fit Interview

At Artefact, we recruit our employees only on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.

Technical Account Managers are highly experienced Architects who bring both deep technical expertise and strong interpersonal skills to support a small portfolio of strategic clients (approximately 3 per TAM). They must be quick on their feet and able to put a positive spin on challenging customer situations, both in the boardroom with a client CTO and while sharing the command line with a client admin. They must be effective technically, both as communicators and doers. They must be capable of managing and maintaining a client relationship, while keeping a tight organizational watch over the technical aspects of their accounts.

How you'll make an impact

• Collaborate with the customer and the internal account team to jointly identify short and long-term priorities and develop the associated engagement plan
• Manage project milestones in partnership with Customer Success Managers and clients, contribute to deliverables, provide regular status updates and proactively identify and mitigate issues and risks
• Serve as a central point for client technical information and contribute to the account strategy alongside the broader account team
• Support the growth and effectiveness of the Field Engineering team through documentation, process improvements, and knowledge sharing
• Act as the primary technical advisor for client teams, providing guidance and hands-on support across a range of areas, including:
  • Dataiku platform architecture and deployment
  • Platform operations and upgrades
  • Best practices for platform usage
  • Security, data management, and compute resources
  • ML-Ops, monitoring, and scaling strategies
• Assist clients in integrating the product into their systems and troubleshoot technical challenges
• Capture client feedback and feature requests to inform the Product and Engineering teams
• Advise client tech leaders on complementary technologies and long-term technical strategy.
• Explore and support advanced use cases involving Dataiku, such as edge computing, deep learning, and MLOps

What you'll need to be successful

• 7+ years of experience in a customer-facing technical role
• Native or bilingual proficiency in German
• Strong communication and client relationship skills
• Experience supporting both pre- and post-sales engagements
• Proficiency in Linux system administration, including networking
• Experience with identity and access management tools (e.g., LDAP, Kerberos, Active Directory, IAM)
• Hands-on experience with cloud platforms (AWS, Azure, GCP)
• Hands-on experience with the Kubernetes ecosystem for setup, administration, troubleshooting and tuning
• Familiarity with the Hadoop and/or Spark ecosystems

How you'll stand out 

• Experience with Python
• Data-Science knowledge
• Basic knowledge of Java
• Familiarity with ML-Ops practices and tools

What does the hiring process look like? #LI-Hybrid #LI-AN1

• Initial call with a member of our Technical Recruiting team
• Video call with the TAM Hiring Manager
• Technical Assessment to show your skills (Home Test)
• Debrief of your Tech Assessment with TAM Team members
• Final Interview with the VP Field Engineering

#LI-JR1

What you’ll do

At Doctolib, we're on a mission to transform the way healthcare is delivered by leveraging the power of AI. As a Machine Learning Engineer, you'll play a critical role in developing and implementing cutting-edge AI solutions that will simplify the access and quality of care for all.

In this role, you'll have the opportunity to work with a team of talented ML Engineers, Software Engineers, MLOps and Healthcare professionals to develop and deploy AI models that will have a real impact on people's lives.

You will work at simplifying how patients find their healthcare practitioner, handle their care plan in the long term and work with business team to contribute expansion of Doctolib in several new markets.

Doctolib is looking for a Machine Learning Engineer to join our ML Engineering team in charge of our patient solutions.

Your responsibilities include but are not limited to:

• Find the right technical solution to solve the product domain goals
• Implement your ideas and test them
• Deploy your algorithms in production guided by our ML platform team
• Measure the uplift and continuously improve your approach 

Who you are

You could be our next team mate if you: 

• Have strong analytical skills, are result oriented and user first
• Have between 3/7 years of experience in the domain of Machine Learning / Deep Learning / AI Engineering, including taking models from prototype to production at scale.
• Have experience in Information Retrieval and modern retrieval stacks, including some of the following:
  • Hybrid search (sparse + dense)
  • Large-scale embeddings and vector databases 
  • Multi-stage retrieval and re-ranking pipelines
  • RAG architectures and retrieval pipelines on multimodal use cases
  • Tools and MCP-based integrations to bring in external data and capabilities
• Proficient in LLM/VLM application development, including:
  • Fine-tuning LLM and VLM models
  • Mixture-of-Experts (MoE) architectures (via LiteLLM or Model Garden)
  • Knowledge Distillation 
  • Prompt engineering and tool use
  • Evaluation and benchmarking of LLM/VLM systems
• Have hands-on experience with agentic AI (e.g. building and orchestrating agents on top of ADK).
• Have demonstrated strong scientific rigor and benchmarking skills:
  
  • Designing metrics aligned with product goals,
  • Running controlled end to end experiments with W&B, MLFlow or Braintrust
  • Analyzing and communicating results to guide product and technical decisions.
• Have experience with large scale applications in production (monitoring, reliability, performance, observability).

Now, it would be fantastic if you: 

• Have experience in B2C marketplace.
• Have experience in other ML methodologies : pattern mining, recommendation, experimentation or causal inference.

What we offer

• Free health insurance for you and your children
• Parent Care Program: receive one additional month of leave on top of the legal parental leave
• Free mental health and coaching services through our partner Moka.care
• For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
• Work from EU countries and the UK for up to 10 days per year, thanks to our flexibility days policy
• Work Council subsidy to refund part of sport club membership or creative class
• Up to 14 days of RTT
• A subsidy from the work council to refund part of the membership to a sport club or a creative class 
• Lunch voucher with Swile card

The interview process 

• HR Screen
• Coding Interview
• System Design Interview
• Behavioral Interview
• Two reference calls and criminal records check 

Job details

• Permanent position 
• Full Time
• Location: Doctolib Paris office in Levallois Perret
• Work mode: Hybrid 3 days/week in the office
• Start date: ASAP

Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here.

Here are some useful links so you preview what we do at Dataiku: Dataiku's Key Capabilities ; Dataiku's Github, you can also take a look at the Gallery, a public instance showcasing some example projects (note editing is very limited and will be regularly reset). 

Our product is called Dataiku DSS which stands for Dataiku Data Science Studio. If you’d like to know more about it, you can watch the demo here or try the free version here.

How you’ll make an impact

This position is either onsite/hybrid from our Berlin office or full remote from any part of Germany.

As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes:

• Data Preparation: Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs.
  • Add new capabilities for data integration, transformation, and visualization using LLMs
  • Optimize workflows for large-scale datasets and improve database support
  • Strengthen developer tools like Jupyter notebooks and SQL workbenches
  • Tech stack: Java, Python, AngularJS, Angular

• AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference.
  • Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models
  • Collaborate with research teams on innovative machine learning experiments
  • Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS

• Data Consumption: build the experience that makes data accessible and actionable for everyone.
  • Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more
  • Create innovative interfaces that answer business questions and surface relevant insights using LLMs
  • Tech stack: Angular, AngularJS, Java, Python

• Data Visualization: elevate our data visualization capabilities with high-performance charting tools and dashboards.
  • Develop new chart types and optimize visualization performance
  • Enhance dash boarding capabilities to deliver fast and flexible experiences
  • Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring
    
    
• MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration.
  • Build tools to automate retraining, monitoring, and deployment of ML models
  • Enhance collaboration features for ML stakeholders
  • Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker
    
    
• Platform: Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines.
  • Optimize processing engines for scalability and latency
  • Expand capabilities to support new databases and cloud platforms
  • Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP
    
    
• AI Governance: Build features for AI compliance, connecting disparate systems and simplifying governance processes.
  • Develop customizable platforms for managing AI compliance and governance
  • Simplify policy enforcement and integration across disparate systems
  • Tech stack: Java, Angular, PostgreSQL

What you need to be successful 

• We’re stack agnostic, so all you need is a significant experience in software engineering,  building a real product
• We’re hiring at all levels (junior, mid, senior)
• A passion for combining backend performance with exceptional frontend user experience.
• You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale

What does the hiring process look like?

• Initial call with a member of our Technical Recruiting team (45min)
• Video call with an Engineering Team Lead (1h30)
• Technical Assessment to show your skills (Home Test or Live Coding)
• Final Interviews with our VPs of Engineering (2h)   #LI-Remote

Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here.

Here are some useful links so you preview what we do at Dataiku: Dataiku's Key Capabilities ; Dataiku's Github, you can also take a look at the Gallery, a public instance showcasing some example projects (note editing is very limited and will be regularly reset). 

Our product is called Dataiku DSS which stands for Dataiku Data Science Studio. If you’d like to know more about it, you can watch the demo here or try the free version here.

How you’ll make an impact

This position is either onsite/hybrid from our Paris office or full remote from any part of France.

As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes:

• Data Preparation: Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs.
  • Add new capabilities for data integration, transformation, and visualization using LLMs
  • Optimize workflows for large-scale datasets and improve database support
  • Strengthen developer tools like Jupyter notebooks and SQL workbenches
  • Tech stack: Java, Python, AngularJS, Angular

• AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference.
• Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models
• Collaborate with research teams on innovative machine learning experiments
• Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS

• Data Consumption: build the experience that makes data accessible and actionable for everyone.
  • Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more
  • Create innovative interfaces that answer business questions and surface relevant insights using LLMs
  • Tech stack: Angular, AngularJS, Java, Python

• Data Visualization: elevate our data visualization capabilities with high-performance charting tools and dashboards.
  • Develop new chart types and optimize visualization performance
  • Enhance dash boarding capabilities to deliver fast and flexible experiences
  • Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring

• MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration.
  • Build tools to automate retraining, monitoring, and deployment of ML models
  • Enhance collaboration features for ML stakeholders
  • Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker
    
    
• Platform: Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines.
  • Optimize processing engines for scalability and latency
  • Expand capabilities to support new databases and cloud platforms
  • Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP
    
    
• AI Governance: Build features for AI compliance, connecting disparate systems and simplifying governance processes.
  • Develop customizable platforms for managing AI compliance and governance
  • Simplify policy enforcement and integration across disparate systems
  • Tech stack: Java, Angular, PostgreSQL

What you need to be successful 

• We’re stack agnostic, so all you need is a significant experience in software engineering,  building a real product
• We’re hiring at all levels (junior, mid, senior)
• A passion for combining backend performance with exceptional frontend user experience.
• You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale

What does the hiring process look like?

• Initial call with a member of our Technical Recruiting team (45min)
• Video call with an Engineering Team Lead (1h30)
• Technical Assessment to show your skills (Home Test or Live Coding)
• Final Interviews with our VPs of Engineering (2h)   #LI-Remote

Who we are

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.

Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.

Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai.

What you will be doing - Key responsibilities

As a Manager Data Scientist, you will play a central role in the design, delivery and scaling of AI projects for our clients. Reporting to the CTO, your responsibilities will include:

• Leading end-to-end client projects: from framing use cases with business stakeholders to implementing AI solutions that generate measurable impact.
• Ensuring technical excellence: promote software engineering and MLOps best practices to deliver scalable solutions and bring them into production.
• Supporting solution design: challenging business requirements, validating data availability, and selecting the most appropriate methodologies and architectures.
• Being the technical reference for clients: explaining AI approaches in simple terms, providing recommendations on feasibility, risks, and ROI.
• Developing trusted client relationships: interacting with C-level and operational teams to position Artefact as a long-term partner on their Data & AI journey.

Beyond these core responsibilities, you will also be involved in:

Managing the country’s data science team

• Support team staffing, ensuring the right skills are applied to meet project needs.
• Ensure each individual’s continuous well-being within the team, supporting their growth through mentoring, coaching, and career development plans.
• Help define the team’s career framework and participate in performance review processes.
• Challenge existing ways of working and drive innovation to continuously improve Artefact’s data science team.

Developing Artefact’s technical expertise

• Contribute to testing and implementing advanced AI approaches and emerging techniques on client use cases.
• Drive initiatives to build internal accelerators, such as modules and tools that can be reused across projects.
• Maintain an active technology watch: evaluate emerging tools, frameworks, and cloud services to assess how they can address client needs.
• Share knowledge through workshops, informal training sessions, and documentation, fostering a culture of continuous learning.

Being a great tech manager

• Lead by example: demonstrate technical rigor, pragmatic problem-solving, and the ability to step in directly on projects when the team needs support.
• Provide constructive feedback to help data scientists in your team progress in both technical and consulting dimensions.
• Anticipate risks and unblock teams, ensuring projects stay on track.
• Balance ambition and feasibility: critically assess approaches, driving innovation while ensuring solutions stay realistic to deliver.
• Foster collaboration between data scientists, data engineers, and business teams to ensure solutions are effectively integrated and adopted.

Qualifications - What we are looking for

• 5+ years of hands-on experience developing data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience with industrializing AI workflows in cloud environments.

In addition to technical expertise, we value individuals who can:

• Lead teams, manage stakeholders, and deliver impactful projects in a business context.
• Show intellectual curiosity and excellent problem-solving skills.
• Tackle challenges with pragmatism and creativity.
• Support growth, mentoring juniors and constructively challenging seniors.
• Earn trust from both peers and business stakeholders.

 Our recruitment process

1. HR call 
2. Standard Interview 
3. Technical Interview 
4. Fit Interview

At Artefact, we recruit our employees solely on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.

Who we are

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.

Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.

Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai.

What you will be doing - Key responsibilities

As a Manager Data Scientist, you will play a central role in the design, delivery and scaling of AI projects for our clients. Reporting to the CTO, your responsibilities will include:

• Leading end-to-end client projects: from framing use cases with business stakeholders to implementing AI solutions that generate measurable impact.
• Ensuring technical excellence: promote software engineering and MLOps best practices to deliver scalable solutions and bring them into production.
• Supporting solution design: challenging business requirements, validating data availability, and selecting the most appropriate methodologies and architectures.
• Being the technical reference for clients: explaining AI approaches in simple terms, providing recommendations on feasibility, risks, and ROI.
• Developing trusted client relationships: interacting with C-level and operational teams to position Artefact as a long-term partner on their Data & AI journey.

Beyond these core responsibilities, you will also be involved in:

Managing the country’s data science team

• Support team staffing, ensuring the right skills are applied to meet project needs.
• Ensure each individual’s continuous well-being within the team, supporting their growth through mentoring, coaching, and career development plans.
• Help define the team’s career framework and participate in performance review processes.
• Challenge existing ways of working and drive innovation to continuously improve Artefact’s data science team.

Developing Artefact’s technical expertise

• Contribute to testing and implementing advanced AI approaches and emerging techniques on client use cases.
• Drive initiatives to build internal accelerators, such as modules and tools that can be reused across projects.
• Maintain an active technology watch: evaluate emerging tools, frameworks, and cloud services to assess how they can address client needs.
• Share knowledge through workshops, informal training sessions, and documentation, fostering a culture of continuous learning.

Being a great tech manager

• Lead by example: demonstrate technical rigor, pragmatic problem-solving, and the ability to step in directly on projects when the team needs support.
• Provide constructive feedback to help data scientists in your team progress in both technical and consulting dimensions.
• Anticipate risks and unblock teams, ensuring projects stay on track.
• Balance ambition and feasibility: critically assess approaches, driving innovation while ensuring solutions stay realistic to deliver.
• Foster collaboration between data scientists, data engineers, and business teams to ensure solutions are effectively integrated and adopted.

Qualifications - What we are looking for

• 5+ years of hands-on experience developing data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience with industrializing AI workflows in cloud environments.

In addition to technical expertise, we value individuals who can:

• Lead teams, manage stakeholders, and deliver impactful projects in a business context.
• Show intellectual curiosity and excellent problem-solving skills.
• Tackle challenges with pragmatism and creativity.
• Support growth, mentoring juniors and constructively challenging seniors.
• Earn trust from both peers and business stakeholders.

 Our recruitment process

1. HR call 
2. Standard Interview 
3. Technical Interview 
4. Fit Interview

At Artefact, we recruit our employees solely on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.

Who we are

Artefact is a new generation of a data service provider, specialising in data consulting and data-driven digital marketing, dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth.

Our broad range of data-driven solutions in data consulting and digital marketing are designed to meet our clients’ specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we’ve acquired with our 1000+ client base around the globe.

We have 850 employees across 20 offices who are focused on accelerating digital transformation. Thanks to a unique mix of company assets: State of the art data technologies, lean AI agile methodologies for fast delivery, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts, all dedicated to bringing extra value to every client.

What you will be doing: 

As a Senior Data Scientist, your role will encompass:

• Leading and conducting ambitious projects in the transformation of clients through data
• Developing data science products and solutions for clients as well as for our data science team
• Working closely with your Consulting counterpart to build and maintain strong relationships with your clients and best understand their needs
• Having a contributor role in upskilling our data science team and promoting our work within the other data departments
• Caring for the happiness of the team, ensuring that missions are delivered to a high standard and providing feedback and mentoring to less experienced Data Scientists
• Writing highly optimised code to advance Artefact’s internal tool box and knowledge

What you will learn with us : 

• Deliver impactful and successful projects on real-world problems across a variety of industries by delivering end-to-end machine learning pipelines
• Build complex solutions in feature teams with the help of your other data scientists but also ML Engineers, Data Engineers, Software Engineers and Product Owners
• Improve your software engineering skills by applying ML Ops best practises and working with the Machine Learning teams
• Become an expert in one of our data science practises: Time Series Forecasting, MLOPs, NLP, Computer Vision, Optimization or Customer Intelligence
• Discover state of the art algorithms and test them during your client projects, on real world data

What we are looking for

• A Doer: you get things done and inspire your teams to do the same
• An Analyst: you LOVE data and think every company should take their decisions with facts
• A Pragmatist: you have a hacker mindset and always find the quick wins
• A Mentor: your clients and teams naturally seek for your advice
• An Adventurer: you’re an entrepreneur constantly looking for problems to solve

Qualifications: Education & experience required

• A Master’s degree in machine learning, mathematics, computer science, or related fields
• 3+ years of hands-on experience developing and applying data-driven solutions in a corporate or consulting setting 
• Strong experience and knowledge of data processing, data modelling, algorithms, and data architecture
• Fluent in at least one of the following languages: Python, R, SQL, etc…
• Experience in leading a technical project in a business context
• Intellectual curiosity and excellent problem-solving skills, including the ability to structure and prioritise an approach for maximum impact

Why you should join us

• Artefact is the place to be: we train the data leaders of tomorrow
• Innovation: every day offers new challenges and new opportunities to learn
• Culture: join the best team you could ever imagine
• Entrepreneurship: you will be joining a team of driven entrepreneurs. We won’t give up until we make a huge dent in this industry!

Still hesitating, check our medium blog to discover concrete projects!

Who we are

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.

Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.

Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai.

What you will be doing - Key responsibilities

As a Manager Data Scientist, you will play a central role in the design, delivery and scaling of AI projects for our clients. Reporting to the CTO, your responsibilities will include:

• Leading end-to-end client projects: from framing use cases with business stakeholders to implementing AI solutions that generate measurable impact.
• Ensuring technical excellence: promote software engineering and MLOps best practices to deliver scalable solutions and bring them into production.
• Supporting solution design: challenging business requirements, validating data availability, and selecting the most appropriate methodologies and architectures.
• Being the technical reference for clients: explaining AI approaches in simple terms, providing recommendations on feasibility, risks, and ROI.
• Developing trusted client relationships: interacting with C-level and operational teams to position Artefact as a long-term partner on their Data & AI journey.

Beyond these core responsibilities, you will also be involved in:

Managing the country’s data science team

• Support team staffing, ensuring the right skills are applied to meet project needs.
• Ensure each individual’s continuous well-being within the team, supporting their growth through mentoring, coaching, and career development plans.
• Help define the team’s career framework and participate in performance review processes.
• Challenge existing ways of working and drive innovation to continuously improve Artefact’s data science team.

Developing Artefact’s technical expertise

• Contribute to testing and implementing advanced AI approaches and emerging techniques on client use cases.
• Drive initiatives to build internal accelerators, such as modules and tools that can be reused across projects.
• Maintain an active technology watch: evaluate emerging tools, frameworks, and cloud services to assess how they can address client needs.
• Share knowledge through workshops, informal training sessions, and documentation, fostering a culture of continuous learning.

Being a great tech manager

• Lead by example: demonstrate technical rigor, pragmatic problem-solving, and the ability to step in directly on projects when the team needs support.
• Provide constructive feedback to help data scientists in your team progress in both technical and consulting dimensions.
• Anticipate risks and unblock teams, ensuring projects stay on track.
• Balance ambition and feasibility: critically assess approaches, driving innovation while ensuring solutions stay realistic to deliver.
• Foster collaboration between data scientists, data engineers, and business teams to ensure solutions are effectively integrated and adopted.

Qualifications - What we are looking for

• 5+ years of hands-on experience developing data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience with industrializing AI workflows in cloud environments.

In addition to technical expertise, we value individuals who can:

• Lead teams, manage stakeholders, and deliver impactful projects in a business context.
• Show intellectual curiosity and excellent problem-solving skills.
• Tackle challenges with pragmatism and creativity.
• Support growth, mentoring juniors and constructively challenging seniors.
• Earn trust from both peers and business stakeholders.

 Our recruitment process

1. HR call 
2. Standard Interview 
3. Technical Interview 
4. Fit Interview

At Artefact, we recruit our employees solely on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.

Your Impact

We are looking for a Senior MLOps Engineer to join the Panda Team (Data & ML Operations) in Data & AI Platform team.

Your mission will be to build and maintain secure ML pipelines in production, transforming how we handle healthcare data at scale. You will work in a feature team developing critical data infrastructure that enables data-driven decision-making while protecting patient privacy across millions of users.

Working in the tech team at Doctolib means building innovative products and features to improve the daily lives of care teams and patients.

What you'll build

Your responsibilities include but are not limited to:

• Design and implement end-to-end ML model pipelines in production (LLM and custom models) with robust deployment, evaluation, and monitoring frameworks
• Own data pseudo-anonymization architecture within ingestion services, converting Tier 0 (personal identifiers) to Tier 1 (anonymized data) while ensuring data quality and model performance
• Build and maintain secure data export services with ML-based threat detection to prevent attack vectors (SQL injection, etc.) using adaptive models rather than manual rules
• Manage golden datasets and implement production model evaluation frameworks to ensure anonymization quality and system reliability
• Build and maintain data pipelines that efficiently extract, transform, and load data from various sources, handling multiple data formats (text, images, audio, video)
• Implement automation and orchestration tools using ML orchestration platforms (MLflow, Braintrust, or similar) to streamline infrastructure provisioning and reduce manual effort
• Monitor data and ML platforms for performance, reliability, and security; identify and troubleshoot issues proactively
• Mentor team members on MLOps expertise and best practices to reduce knowledge silos and build organizational capability

Life at Doctolib Tech

• Our solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to country and healthcare specialty requirements.
• Our stack is composed of Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native.
• We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here.

Want to learn more about our tech culture and environment? Visit the Doctolib Tech site.

What you'll bring

Before you read on: if you don't have the exact profile described below, but you feel this job description matches your skill set, we still encourage you to apply.

You'll be a great fit if you:

• You have at least 7+ years as an MLOps Engineer or ML Platform Engineer with proven production model lifecycle management experience
• You have expert-level experience with ML orchestration tools (MLflow, Braintrust, or similar) for batch processing and inference pipelines
• You have a strong Site Reliability Engineering (SRE) foundation with focus on operations excellence, reliability, and observability
• You have expertise in Python for automation and ML pipeline scripting
• You have strong proficiency with infrastructure-as-code tools such as Terraform and container orchestration (Kubernetes)
• You have experience with model evaluation frameworks and golden dataset management
• You have a solid understanding of cloud infrastructure (preferably GCP, AWS, or Azure)
• You have excellent problem-solving skills with focus on identifying and resolving infrastructure bottlenecks
• You are fluent in English

It would be fantastic if you:

• Have production LLM or custom model deployment experience
• Have knowledge of data security and privacy frameworks (GDPR, data anonymization, pseudonymization)
• Have experience building and monitoring security services and threat detection systems
• Have strong communication and mentoring skills to drive knowledge transfer across teams

What we offer

• Free comprehensive health insurance for you and your children
• 25 days of paid vacation per year, plus up to 14 days of RTT
• Free mental health and coaching services through our partner Moka.care
• Work from abroad for up to 10 days per year thanks to our flexibility days policy
• Lunch vouchers (Swile card) worth €8.50 per working day, with €4.50 covered by Doctolib
• A subsidy from the work council to refund part of the membership to a sport club or a creative class
• 50% reimbursement of your public transport subscription
• Parent Care Program: receive one additional month of leave on top of the legal parental leave
• For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
• Relocation support in case of international mobility
• Access to the best AI tools for coding, development and dedicated training

Our interview process

• Recruiter Interview
• Technical Case Study Interview 
• System Design Interview 
• Behavioral Interview
• At least one reference check

We want your experience to be clear, respectful, and transparent. Learn more about our hiring process on our candidate experience page.

Job details

• Permanent position (CDI)
• Tech stack: Python
• Full-time
• Nantes & Paris (Hybrid Policy: 2 days remote / week)
• Start date: as soon as possible

We welcome everyone

At Doctolib, we are committed to improving access to healthcare for everyone. This translates into our recruitment process. We evaluate candidates based solely on qualifications and motivation, without any form of discrimination.

The more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, or disability.

To ensure equal opportunities, we invite you to exclude personal information (e.g., pictures, age) from your applications. If you require any accommodation, please let us know for support during the hiring process.

Join us in building the healthcare we all dream of!

Your data privacy

All information provided is processed by Doctolib for application management. For data processing details, click here: France. Please contact hr.dataprivacy(at)doctolib.com for inquiries or to exercise your rights.

Are you passionate about artificial intelligence and want to contribute to revolutionizing the healthcare sector? Doctolib develops cutting-edge AI solutions to improve access to care and facilitate the daily lives of healthcare professionals and patients. Our AI/ML teams work on large-scale projects: medical natural language processing, recommendation systems, clinical process automation, and much more.

We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here!

By joining our AI talent pool, you will be contacted as a priority for our future opportunities in the following areas:

The areas of expertise we are looking for :

• ML Engineering & MLops : Python proficiency, Model deployment, Evaluation frameworks (Offline/Online) & Model monitoring
• Natural Language Process (NLP) : Clinical NLP, LLM expertise Deep Learning or Speech / Language modeling 
• LLMops & Generative AI : Prompt Engineering, RAG, LLM fine-tuning, Embedding models, Agent frameworks 
• Automatic Speech Recognition (ASR) : Voice Activity Detection, Interactive voice assistants, audio processing, Speech-to-text 
• Search, Ranking, information retrieval
• Reasoning capabilities  : Logical reasoning, Multi-step reasoning, Chain-of-thought approaches
• Knowledge representation : Knowledge graphs, ontologies, Semantic modeling 
• Reinforcement Learning : RL algorithms, Policy optimization, Reward modeling

Most of our positions require:

Before reading further, if you don't have the exact profile described below, but you think this job description matches your skills and aspirations, we still encourage you to apply.

• Hold a degree in computer science, applied mathematics, data science, or related field (Master's, PhD, or equivalent)
• Master machine learning and deep learning frameworks (PyTorch, TensorFlow, Scikit-learn)
• Have hands-on experience with LLMs, open and closed source  Proficient in Python
• Possess strong analytical skills and a results-oriented approach
• You speak English fluently (international work environment)

It would be fantastic if:

• You have experience in healthcare or medical NLP
• You master RAG techniques, embeddings, and vector search
• You know MLOps technologies and model deployment in production (Kubernetes, Docker, MLflow)
• You have contributed to open-source projects or published in AI conferences

At Doctolib, we believe in improving access to healthcare for everyone - regardless of where you come from, what you look like. This translates into our recruitment process: Doctolib is an equal opportunity employer. We don't just accept diversity at Doctolib, we respect and celebrate it!

The more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, disability, or place of origin. If you have a disability, let us know if there's any way we can make the interview process smoother for you! 

All the information transmitted via this form is processed by Doctolib for the purpose of managing applications. For more information on how Doctolib processes your application data, click here.

If you wish to exercise your rights or if you have any questions about the processing of your data, you can write to us at hr.dataprivacy@doctolib.com.

L'équipe Data Platform de DECATHLON recherche un·e Senior MLOPS basé·e·s à Lille/Paris. 

Au cœur de l’entité Decathlon Digital, nous recherchons un·e Senior MLOPS pour rejoindre les équipes Data Factory.

Cette plateforme technologique, globale à tout le groupe de manière internationale, soutient le développement de l’usage de la Data chez Decathlon, du calcul du chiffre d’affaires à l’aide de conception de produits innovants.

Nous opérons une Modern Data Stack de pointe, avec un Lakehouse comme centre de gravité. Notre mission ? Garantir la scalabilité, l'automatisation et l'excellence des pratiques de développement pour l'ensemble de nos communautés (Data Engineers, Analysts, Scientists).

Notre équipe IA / MLOPS au cœur de la Data Factory est une brique essentielle de cette mission. Elle est chargée d’outiller les data scientists, ML engineers pour mener à bien leur mission. De plus elle joue un rôle centrale dans la mise à disposition de LLM et d’agents à nos utilisateurs techniques

TA FUTURE CONTRIBUTION 

En tant que Senior MLOps, au sein de la squad IA / ML tu joueras un rôle clé pour outiller les data scientists et ML engineers afin de les aider à mener à bien leur mission. De plus, tu auras un rôle central dans la mise à disposition des technologies d'IA générative pour nos développeurs. L’équipe est composée de 4 MLOPS et de 2 Product Managers.

Tu seras en charge de:

• Design & Architecture Multi-Cloud : Concevoir des architectures IA robustes et sur-mesure sur AWS et GCP, en étant force de proposition pour répondre aux besoins spécifiques de nos utilisateurs.
• Industrialisation & IaC : Piloter le déploiement, le maintien et l'évolution de nos infrastructures IA via Terraform, en garantissant une cohérence parfaite entre nos différents environnements Cloud.
• Automatisation & CI/CD : Optimiser nos cycles de mise en production en orchestrant des pipelines de déploiement continu (CI/CD) via Git, assurant ainsi rapidité et fiabilité.
• Gouvernance & Excellence : Définir les standards de demain en créant des guides, des templates et des bonnes pratiques, tout en assurant une veille stratégique (IA & GenAI) pour maintenir notre avantage technologique.
• Expertise & Rayonnement : Incarner nos solutions auprès des équipes techniques et métiers, notamment en animant des Office Hours et en vulgarisant les enjeux complexes de la plateforme

STACK TECHNIQUE

• Cloud AWS et GCP
• Databricks
• MLFlow
• Airflow
• Terraform
• Docker, Kubernetes

CE QUE TU APPORTES

• Pédagogie et Sens du service : Tu sais accompagner les utilisateurs avec clarté, traduire des concepts IA complexes en solutions techniques simples, et rédiger une documentation robuste.
• Curiosité : La veille technologique fait partie de ton ADN

• Esprit collaboratif : Tu t'épanouis dans un environnement agile où le partage est la règle 
• Communication : Un excellent relationnel pour fédérer autour de tes solutions. Ton anglais est fluide pour évoluer dans notre contexte international.
• Expérience : Tu justifies de 3 ans minimum d’expérience sur un rôle similaire (MLOps, ML engineer)

L'équipe Data Platform de DECATHLON recherche un·e Senior MLOPS basé·e·s à Lille/Paris. 

Au cœur de l’entité Decathlon Digital, nous recherchons un·e Senior MLOPS pour rejoindre les équipes Data Factory.

Cette plateforme technologique, globale à tout le groupe de manière internationale, soutient le développement de l’usage de la Data chez Decathlon, du calcul du chiffre d’affaires à l’aide de conception de produits innovants.

Nous opérons une Modern Data Stack de pointe, avec un Lakehouse comme centre de gravité. Notre mission ? Garantir la scalabilité, l'automatisation et l'excellence des pratiques de développement pour l'ensemble de nos communautés (Data Engineers, Analysts, Scientists).

Notre équipe IA / MLOPS au cœur de la Data Factory est une brique essentielle de cette mission. Elle est chargée d’outiller les data scientists, ML engineers pour mener à bien leur mission. De plus elle joue un rôle centrale dans la mise à disposition de LLM et d’agents à nos utilisateurs techniques

TA FUTURE CONTRIBUTION 

En tant que Senior MLOps, au sein de la squad IA / ML tu joueras un rôle clé pour outiller les data scientists et ML engineers afin de les aider à mener à bien leur mission. De plus, tu auras un rôle central dans la mise à disposition des technologies d'IA générative pour nos développeurs. L’équipe est composée de 4 MLOPS et de 2 Product Managers.

Tu seras en charge de:

• Design & Architecture Multi-Cloud : Concevoir des architectures IA robustes et sur-mesure sur AWS et GCP, en étant force de proposition pour répondre aux besoins spécifiques de nos utilisateurs.
• Industrialisation & IaC : Piloter le déploiement, le maintien et l'évolution de nos infrastructures IA via Terraform, en garantissant une cohérence parfaite entre nos différents environnements Cloud.
• Automatisation & CI/CD : Optimiser nos cycles de mise en production en orchestrant des pipelines de déploiement continu (CI/CD) via Git, assurant ainsi rapidité et fiabilité.
• Gouvernance & Excellence : Définir les standards de demain en créant des guides, des templates et des bonnes pratiques, tout en assurant une veille stratégique (IA & GenAI) pour maintenir notre avantage technologique.
• Expertise & Rayonnement : Incarner nos solutions auprès des équipes techniques et métiers, notamment en animant des Office Hours et en vulgarisant les enjeux complexes de la plateforme

STACK TECHNIQUE

• Cloud AWS et GCP
• Databricks
• MLFlow
• Airflow
• Terraform
• Docker, Kubernetes

CE QUE TU APPORTES

• Pédagogie et Sens du service : Tu sais accompagner les utilisateurs avec clarté, traduire des concepts IA complexes en solutions techniques simples, et rédiger une documentation robuste.
• Curiosité : La veille technologique fait partie de ton ADN

• Esprit collaboratif : Tu t'épanouis dans un environnement agile où le partage est la règle 
• Communication : Un excellent relationnel pour fédérer autour de tes solutions. Ton anglais est fluide pour évoluer dans notre contexte international.
• Expérience : Tu justifies de 3 ans minimum d’expérience sur un rôle similaire (MLOps, ML engineer)

L'équipe Data Platform de DECATHLON recherche un·e Senior MLOPS basé·e·s à Lille/Paris. 

Au cœur de l’entité Decathlon Digital, nous recherchons un·e Senior MLOPS pour rejoindre les équipes Data Factory.

Cette plateforme technologique, globale à tout le groupe de manière internationale, soutient le développement de l’usage de la Data chez Decathlon, du calcul du chiffre d’affaires à l’aide de conception de produits innovants.

Nous opérons une Modern Data Stack de pointe, avec un Lakehouse comme centre de gravité. Notre mission ? Garantir la scalabilité, l'automatisation et l'excellence des pratiques de développement pour l'ensemble de nos communautés (Data Engineers, Analysts, Scientists).

Notre équipe IA / MLOPS au cœur de la Data Factory est une brique essentielle de cette mission. Elle est chargée d’outiller les data scientists, ML engineers pour mener à bien leur mission. De plus elle joue un rôle centrale dans la mise à disposition de LLM et d’agents à nos utilisateurs techniques

TA FUTURE CONTRIBUTION 

En tant que Senior MLOps, au sein de la squad IA / ML tu joueras un rôle clé pour outiller les data scientists et ML engineers afin de les aider à mener à bien leur mission. De plus, tu auras un rôle central dans la mise à disposition des technologies d'IA générative pour nos développeurs. L’équipe est composée de 4 MLOPS et de 2 Product Managers

Tu seras en charge de:

• Design & Architecture Multi-Cloud : Concevoir des architectures IA robustes et sur-mesure sur AWS et GCP, en étant force de proposition pour répondre aux besoins spécifiques de nos utilisateurs.
• Industrialisation & IaC : Piloter le déploiement, le maintien et l'évolution de nos infrastructures IA via Terraform, en garantissant une cohérence parfaite entre nos différents environnements Cloud.
• Automatisation & CI/CD : Optimiser nos cycles de mise en production en orchestrant des pipelines de déploiement continu (CI/CD) via Git, assurant ainsi rapidité et fiabilité.
• Gouvernance & Excellence : Définir les standards de demain en créant des guides, des templates et des bonnes pratiques, tout en assurant une veille stratégique (IA & GenAI) pour maintenir notre avantage technologique.
• Expertise & Rayonnement : Incarner nos solutions auprès des équipes techniques et métiers, notamment en animant des Office Hours et en vulgarisant les enjeux complexes de la plateforme

STACK TECHNIQUE

• Cloud AWS et GCP
• Databricks
• MLFlow
• Airflow
• Terraform
• Docker, Kubernetes

CE QUE TU APPORTES

• Pédagogie et Sens du service : Tu sais accompagner les utilisateurs avec clarté, traduire des concepts IA complexes en solutions techniques simples, et rédiger une documentation robuste.
• Curiosité : La veille technologique fait partie de ton ADN

• Esprit collaboratif : Tu t'épanouis dans un environnement agile où le partage est la règle 
• Communication : Un excellent relationnel pour fédérer autour de tes solutions. Ton anglais est fluide pour évoluer dans notre contexte international.
• Expérience : Tu justifies de 3 ans minimum d’expérience sur un rôle similaire (MLOps, ML engineer)