The role

Nebius seeks a Key Customers Solutions Architect to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy, and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work remotely from Europe.

Your responsibilities will include: 

• Serve as the primary technical point of contact, troubleshooting and resolving complex AI/ML.
• Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
• Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
• Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
• Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

We expect you to have:

• Experience: 5 - 10 + years in roles like Cloud Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
• Experience with Kubernetes and Python programming.
• Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
• Customer-centric approach with a proven ability to build trust and foster long-term relationships.
• Strong ability to explain technical concepts to technical and non-technical audiences.

It will be an added bonus if you have:

• Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
• Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
• Proven experience mentoring technical teams and driving team growth.
• Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

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

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 are looking for a Customer Engineer to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy, and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work remotely from Europe.

Your responsibilities will include:

• Serve as the primary technical point of contact for troubleshooting and resolving complex AI/ML issues.
• Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
• Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
• Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
• Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

We expect you to have:

• Experience: 5+ years in roles like Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
• Experience with Kubernetes and Python programming.
• Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
• Customer-centric approach with a proven ability to build trust and foster long-term relationships.
• Strong ability to explain technical concepts to technical and non-technical audiences.

It will be an added bonus if you have:

• Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
• Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
• Proven experience mentoring technical teams and driving team growth.
• Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

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 team

Customer experience at Nebius GPU 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 seeking a highly skilled and customer-focused leader to join our team as a Cloud Solutions Architect Lead. As a team leader, you will play a pivotal role in customer success across EU region, both managing the efforts of Cloud Solutions Architects team (technical and process excellence, talent development) and building processes alongside your stakeholders. Player-coach mentality and proven track record of managing high expertise teams is a must. 

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

Your responsibilities will include: 

• Lead and mentor a team of Solutions Architects, fostering a culture of technical excellence, customer empathy, and collaborative execution.
• Oversee and participate in technical engagements including PoCs, workshops, architecture reviews, and trainings.
• Drive consistency and quality across infrastructure design, IaC practices, technical documentation, and customer enablement content.
• Collaborate closely with Product and Development teams, representing customer needs and helping shape the roadmap.
• Guide customers in optimizing ML/AI/HPC pipelines for performance, scalability, and cost-efficiency on Nebius  cloud infrastructure.
• Build visibility and ownership culture amongst Solutions Architects.

We expect you to have: 

• 5+ years of experience in a technical role (Solutions Architect, DevOps Engineer, ML Engineer, or similar) with a focus on cloud-native systems and distributed computing.
• 2+ years of experience leading or mentoring customer facing engineering teams.
• Deep hands-on experience with Infrastructure as Code (Terraform, Ansible), Kubernetes, and cloud automation.
• Strong communication and stakeholder management skills across both technical and non-technical audiences.
• Passion for developing scalable, reliable cloud architectures and driving customer success.

It will be an added bonus if you have: 

• Experience with HPC or ML orchestration frameworks (e.g., Slurm, Kubeflow, Ray).
• Strong coding skills in Python and experience with GPU computing environments for ML/AI workloads.
• Proficient in GPU stack components (e.g., CUDA, cuDNN) and cloud-native patterns for ML training/inference.
• Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX).
• Understanding of cloud-based ML tools and offerings from NVIDIA, AWS, Azure, or Google Cloud.
• Experience participating in or leading technical contributions to conferences or open-source communities. 

Why Cast AI?

Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production.
The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation.
Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS.

Global team, diverse perspectives

We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead.

Unicorn momentum

In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started.

Join us as we build the future of autonomous infrastructure.

About the role

Throughput. Latency. KV cache utilization.

Move those three numbers in the right direction, and two things happen: customers get faster, cheaper inference, and our margins improve. That's the entire thesis of this role. Every kernel you tune, every quantization scheme you ship, every scheduler tweak you land shows up directly in a customer's p99 and on our P&L.
This is a high-impact seat. It is also a high-autonomy seat as you'll be given the room to lead the technical direction of inference optimization at Kimchi, not execute someone else's roadmap.

The problem: running LLMs in production is a moving target. The "right" model and serving configuration for a workload depend on traffic shape, sequence-length distribution, batch dynamics, GPU SKU, memory bandwidth, quantization tolerance, and a dozen other variables that shift week to week. Most teams pick a model once, over-provision GPUs, and absorb the cost. Kimchi is the system that makes that decision automatically - continuously matching workloads to the most cost-efficient, best-performing LLM and serving configuration on a customer's infrastructure. We're building the optimization layer between the model and the hardware, and we need engineers who understand both sides deeply.

Stack

Python; vLLM; SGLang; TensorRT-LLM; PyTorch; CUDA-adjacent tooling; Kubernetes; gRP; ClickHouse; PostgreSQL; GCP Pub/Sub; AWS / GCP / Azure; GitLab CI; ArgoCD; Prometheus; Grafana; Loki; Tempo.

Requirements:

• 5+ years building real ML systems, with a portfolio that shows depth in inference or training infrastructure (not just model training notebooks).
• Strong Python - production services, not scripts.
• Hands-on experience with at least one of vLLM, SGLang, or TensorRT-LLM, and a working mental model of why an inference engine performs the way it does on a given GPU.
• Fluency with quantization tradeoffs - you've measured quality regressions, not just compression ratios.
• Comfort with distributed systems: collective communication, sharding strategies, and the practical failure modes of multi-GPU and multi-node setups.
• A bias toward measurement. You instrument before you optimize, and you can tell the difference between a real win and a benchmark artifact.
• Self-direction. This role comes with a wide mandate; you should be excited by that, not unsettled by it.

Responsibilities:

• Push throughput. Continuous batching, speculative decoding, chunked prefill, kernel-level tuning across vLLM, SGLang, and TensorRT-LLM. Find the ceiling on each GPU SKU, then raise it.
• Cut latency. Attack TTFT and TPOT separately. Profile, identify the actual bottleneck (compute, memory bandwidth, scheduling, networking), and fix it - not the bottleneck you assumed.
• Get more out of the KV cache. Paged attention, prefix caching, eviction policies, cache reuse across requests, quantized KV. This is where a lot of the unrealized throughput lives, and it's an area you'll own.
• Quantize without regressing quality. INT8, INT4, FP8 across weights, activations, and KV. Empirical work: measure quality on real workloads, not just perplexity benchmarks.
• Shrink cold starts and memory footprint. Faster init, smarter weight loading, tighter memory accounting - the difference between a model that scales and one that doesn't.
• Scale across nodes. Distributed inference topologies, network-aware placement, checkpointing strategies that don't bottleneck on storage or interconnect.
• Set the technical direction. Decide what we benchmark, what we adopt, and what we build ourselves. Bring the team along with strong writeups and reproducible experiments.

What’s in it for you?

• Competitive salary (depending on the level of experience).
• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Annual hackathon to spark new ideas and strengthen team bonds.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

Hiring process

• Screening call with Recruiter
• Hiring Manager interview
• Technical interview (system design)
• Live coding
• Culture Check interview with an executive

As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
Please note that Cast AI does not provide any form of visa sponsorship/work permit.

#LI-Remote

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 ! 🚀

What You Will Do

At Doctolib, we're revolutionizing healthcare delivery through advanced AI systems focused on medical reasoning. As a Senior Staff Research Scientist, you'll develop cutting-edge AI solutions that enhance clinical decision-making and support healthcare professionals in their daily practice. You'll work at the intersection of machine learning and healthcare, creating models that can understand medical knowledge, reason through complex clinical scenarios, and assist medical practitioners in providing better care.

Your responsibilities include (but are not limited to):

• Solve Real-World Healthcare Challenges: Design and build advanced machine learning models, especially in NLP and large language models, to improve healthcare workflows, enhance patient experiences, and power intelligent health solutions at scale.
• Innovate & Experiment: Research and prototype novel algorithms and architectures, staying at the forefront of AI/ML developments. Bring new ideas from concept to working prototypes, leveraging the latest advances in deep learning and generative AI.
• Collaborate Across Teams: Work closely with product, engineering, medical experts, and other stakeholders to translate business needs into impactful research projects. Communicate technical concepts and results clearly to both technical and non-technical audiences.
• Drive Impact: Analyze large, complex data sets to extract actionable insights, define key metrics, and rigorously evaluate model performance.
• Share & Learn: Advance Doctolib’s AI expertise by sharing findings within the team and with the wider ML community through publications, talks, and workshops. Mentor and support other scientists and engineers in adopting best practices.

Who You Are

• Technical Expertise:
• PhD or Master’s degree (plus significant experience) in Computer Science, Machine Learning, Mathematics, or a related field; Publications as first author in top-tier AI/ML conferences such as NeurIPS, ICLR, ICML, ACL, EMNLP, or relevant medical informatics venues are a plus;
• Deep understanding of machine learning and deep learning concepts, with hands-on experience in NLP, LLMs, or generative AI.
• Strong programming skills in Python (and ideally experience with ML frameworks such as PyTorch or JAX).
• Familiarity with modern data tools and scalable training on large datasets.
• Innovator & Problem Solver:
• Track record of independently driving research and translating it into real-world applications.
• Experience designing experiments, evaluating intrinsic and extrinsic metrics, and iterating quickly.
• Curiosity and drive to learn, research, and apply new machine learning techniques.
  
  
• Collaborative & Communicative:
• Comfortable working in highly cross-functional teams, with the ability to clearly communicate complex concepts to diverse audiences.
• Passionate about sharing knowledge and contributing to a culture of learning and innovation.
  
  
• Mission-Driven:
• Motivated by Doctolib’s mission to make healthcare better for all. Eager to solve meaningful problems with technology.
• Detail-oriented, rigorous, and committed to delivering high-quality, production-ready solutions.

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

 The interview process  

• HR Screen 
• Call with Research Team Member 30 mins
• Scientific Presentation + Case Study 1 hour 30mins
• Behavioral Interview 1 hour 15mins
• At least one Reference 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

If you would like to find out more about tech life at Doctolib, feel free to read our latest Medium blog articles!

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, 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!

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

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 ! 🚀

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products.

Building on our track record of AI-powered solutions (e.g., Bits AI, Bits Evolve, and our time series foundation model), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security.

We are focused on two research areas:

1. World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents.
2. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost.

What You'll Do:

• Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability
• Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure
• Design and build simulated environments and RL training loops for on-policy agent training and evaluation
• Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products
• Stay at the forefront of foundation models, world models, and RL-based agent research
• Contribute to research publications, present at top-tier conferences (e.g., NeurIPS, ICLR, ICML), and help open-source key model artifacts and benchmarks

Who You Are:

• You hold a PhD in Computer Science, Machine Learning, or a related field, with deep expertise in areas like generative modeling, world models, AI agents, reinforcement learning, or multimodal learning (or have equivalent experience)
• You have extensive experience designing and implementing deep learning models and agents, with a strong background in distributed training frameworks (e.g., DeepSpeed, Megatron-LM) and ML libraries (PyTorch)
• You have a track record of impactful publications at top-tier venues (e.g., NeurIPS, ICLR, ICML, TMLR)
• You are familiar with efficient training, post-training, and inference techniques for large foundation models
• You can explain complex models and research findings to both technical and non-technical audiences

Bonus Points (any of the following):

• Experience bridging research and real-world product applications, especially with large foundation models, world models, or RL-trained agents
• Passion for pushing the boundaries of AI with a focus on customer impact and scalable deployment
• Experience writing production data pipelines and applications
• Hands-on experience with GPU programming and optimization, including CUDA

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:

• Competitive global benefits 
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Opportunity to collaborate closely with colleagues across the Datadog offices in New York City and Paris
• Opportunity to attend and present at conferences and meetups
• Intra-departmental mentor and buddy program for in-house networking
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)

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

About Datadog: 

Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.

Equal Opportunity at Datadog:

Datadog is an Affirmative Action and Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.

Your Privacy:

Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice.

#LI-Hybrid

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production.

Building on our track record of AI-powered solutions (e.g., Bits AI, Bits Evolve, and our time series foundation model), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security.

We are focused on two research areas:

1. World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents.
2. Trained Agents for Observability-- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost.

What You'll Do:

• Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling
• Implement models, run experiments at scale, and profile for reliability, performance, and cost
• Build simulation environments and replay infrastructure for agent training and evaluation
• Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery
• Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity
• Collaborate with Research Scientists, Product, and Engineering to integrate capabilities into Datadog's products and to harden prototypes into reliable services
• Contribute to research publications at top-tier conferences (e.g., NeurIPS, ICLR, ICML), and produce high-quality code, documentation, and open-source artifacts

Who You Are:

• You have depth in distributed computing, RL Infra, and ML systems for training and inference at scale; experience with Ray, Slurm, or similar frameworks is a plus
• You are proficient in Python, familiar with a systems language (e.g., Rust, C++, or Go), and comfortable with modern cloud and data infrastructure
• You have practical experience implementing and operating ML training and inference systems (e.g., PyTorch or JAX), including containerization, orchestration, and GPU acceleration
• You have practical experience with large-scale model training and fine-tuning, including frameworks like Megatron-LM, DeepSpeed, SkyRL, VeRL, or TorchTitan, and techniques such as SFT, RLVR, RLHF, and efficient inference (quantization, speculative decoding)
• You can explain design and performance trade-offs clearly to both technical and non-technical audiences
• You have experience supporting or contributing to research publications

Bonus Points (any of the following):

• You have strong software engineering skills with experience in domains such as observability, SRE, or security
• You have experience bridging research prototypes and real-world product applications, especially with large foundation models, world models, or RL-trained agents
• You have a passion for pushing the boundaries of AI with a focus on customer impact and scalable deployment
• You have hands-on experience with GPU programming and optimization, including CUDA
• You have experience writing production data pipelines and applications
• You have experience building simulation or sandbox environments for agent training

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:

• Competitive global benefits 
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Opportunity to collaborate closely with colleagues across the Datadog offices in New York City and Paris
• Opportunity to attend and present at conferences and meetups
• Intra-departmental mentor and buddy program for in-house networking
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)

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

About Datadog: 

Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.

Equal Opportunity at Datadog:

Datadog is an Affirmative Action and Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.

Your Privacy:

Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice.

#LI-hybrid

Notre Team Digital Analytics recherche un·e Senior Data Scientist (f/m/d) basé·e à Paris ou Lille.

L'équipe Digital Analytics est le moteur de la décision basée sur la donnée pour l'Ecommerce de Decathlon. Composée d'experts en analytics, expérimentation et data science, notre mission est de transformer la donnée brute en leviers de croissance. Nous relevons des défis de personnalisation à l'échelle mondiale et d'optimisation du parcours client pour rendre le sport accessible au plus grand nombre. Rejoindre notre équipe, c'est intégrer un environnement stimulant où vos modèles ont un impact direct sur des millions d'utilisateurs.

TA FUTURE CONTRIBUTION

En tant que Senior Data Scientist, tu joues un rôle clé dans l'exploration des données et la création d'expériences produits intelligentes. Tes missions incluent :

• Concevoir des solutions de Data Science & Analytics Avancée : Développer des modèles de Machine Learning (prédictifs et prescriptifs) pour résoudre des problématiques complexes liées à l'expérience client.

• Piloter des cas d'usage de bout en bout : De la découverte du problème au déploiement et à l'optimisation continue, tu es garant·e de la pertinence et de la précision de tes solutions.

• Explorer et identifier des opportunités : Analyser proactivement les comportements et tendances pour déceler des leviers d'impact majeurs.

• Collaborer pour la mise en production : Travailler main dans la main avec les Product Managers et ingénieurs pour assurer la scalabilité et la fiabilité des solutions.
  
  

CE QUE TU APPORTES

• Expertise End-to-End : Tu maîtrises tout le cycle de vie d'un projet data (feature engineering, modélisation, monitoring).

• Culture Produit & Impact : Tu sais traduire des analyses complexes en recommandations actionnables pour le business.

• Maîtrise de l'Expérimentation : Expérience solide en design et analyse de tests A/B ou multivariés.

• Communication : Capacité à vulgariser des concepts techniques auprès de parties prenantes variées.

• Bon niveau en anglais, écrit, oral

STACK TECHNIQUE

• Langages & Frameworks : Python (Pandas, Scikit-learn), SQL, Spark / PySpark.

• Environnement : Databricks, Jupyter Notebooks, Git, MLflow.

• Outils Analytics : Statsig, Amplitude, Tableau.

• Bonus : TensorFlow, PyTorch.
  
  

CE QUE NOUS T’OFFRONS

• Organisation de travail hybride ;

• Matériel fourni en accord avec tes missions et nos engagements sociétaux (Mac ou Windows) ;

• Une équipe de projet locale au sein d'un réseau mondial (possibilité de carrière internationale) ;

• Développement des compétences et accompagnement (diversité des projets, formations internes et externes, etc.) ;

• Package de rémunération (actionnariat salarié, bonus mensuels/trimestriels).
  
  

NOTRE ENGAGEMENT EN FAVEUR DE L'INCLUSION ET DE L'ACCESSIBILITE

Chez Decathlon, nous reconnaissons l'immense valeur qu'apporte la diversité à nos équipes et nous nous efforçons continuellement de favoriser et de cultiver un lieu de travail inclusif et équitable : c'est pourquoi l'Inclusion est l'un de nos Fondamentaux Humains. Nous encourageons les personnes de tous horizons et de toutes capacités à postuler, car nous sommes convaincu·es que la diversité des pensées, des cultures, des identités et des expériences vécues nous rend plus fort·es. Decathlon s'engage également à offrir un processus de sélection inclusif et accessible à tous les candidat·es. En cas de besoin d'aménagement, tu peux en faire la demande via le formulaire de candidature, celle-ci sera confidentielle. Ces demandes n'affectent pas le résultat du processus de recrutement.

We are looking for a Senior Data Scientist (f/m/d) to join the Digital Analytics team within Ecommerce.

The Digital Analytics team enables data-informed decision-making across Decathlon ecommerce, driving faster and smarter outcomes. We go beyond descriptive analytics by combining advanced analytics, experimentation, and data science to both understand and shape customer behavior. By embedding these capabilities into our digital products, we power intelligent features, personalization, and continuous optimization at scale. By integrating data across the full product lifecycle, we ensure every feature and iteration delivers meaningful value for both users and the business.

As a Senior Data Scientist, you will play a key role in exploring data, generating insights, and building data-powered product experiences. You will partner closely with product managers, engineers, and analysts to apply predictive and prescriptive analytics, and develop models that directly impact customer experience and business performance.

This is a highly product-oriented role: we are looking for someone who combines strong analytical thinking with applied data science, and who has hands-on experience delivering solutions in real-world product environments. You should be comfortable moving from exploration and hypothesis generation to modeling and impact measurement, with a focus on delivering tangible outcomes in a product environment.

YOUR FUTURE CONTRIBUTION

As a Senior Data Scientist, you will play a key role in exploring data, generating insights, and building data-powered product experiences. You will partner closely with product managers, engineers, and analysts to apply predictive and prescriptive analytics, and develop models that directly impact customer experience and business performance.

• Build data science & advanced analytics solutions: Develop machine learning models and apply predictive and prescriptive analytics to solve complex ecommerce and customer experience problems.
• Own end-to-end use cases: Translate business and product requirements into clear data science approaches. Take full ownership from problem discovery to modeling, deployment, and ongoing refinement.
• Explore & identify opportunities: Proactively analyze data to uncover customer behaviors, trends, and high-impact opportunities.
• Collaborate to deliver in production: Partner closely with product and engineering to bring solutions live, ensuring scalability, reliability, and business impact.

WHAT YOU BRING

• End-to-end Data Science Ownership: Experience across the entire lifecycle (discovery, feature engineering, modeling, experimentation, deployment).
• Applied Data Science: Strong ability to apply statistical modeling and machine learning to real-world product problems like conversion optimization or personalization.
• Product expertise: Experience working in product environments with a focus on optimizing customer journeys.
• Technical Proficiency: Strong programming skills in Python (pandas, scikit-learn) and large-scale data tools (SQL, Spark).
• Collaboration: Proven ability to partner with diverse stakeholders and communicate insights effectively.

TECHNICAL STACK

• Languages & Frameworks : Python (Pandas, Scikit-learn), SQL, Spark / PySpark.

• Environnement : Databricks, Jupyter Notebooks, Git, MLflow.

• Analytics Tools : Statsig, Amplitude, Tableau.

• Bonus : TensorFlow, PyTorch.

WHAT WE OFFER

• Hybrid work organization;
• Equipment provided in line with your missions and our societal commitments (Mac or Windows);
• A local project team within a global network (international career opportunities);
• Skills development and support (diversity of projects, internal and external training, etc.);
• Remuneration package (employee shareholding, monthly/quarterly bonuses).
  
  

OUR COMMITMENT TO INCLUSION AND ACCESSIBILITY

At Decathlon, we recognize the immense value that diversity brings to our teams and we continuously strive to foster and cultivate an inclusive and equitable workplace: this is why Inclusion is one of our Human Fundamentals. We encourage people of all backgrounds and abilities to apply, as we are convinced that diversity of thoughts, cultures, identities and lived experiences makes us stronger. Decathlon is also committed to offering an inclusive and accessible selection process to all candidates. If you need adjustment, you can request it via the application form, it will be confidential. These requests do not affect the outcome of the recruitment process.

Research Scientist in Science

Founded in 2014, InstaDeep is today an EMEA leader in decision-making AI products for the Enterprise, with headquarters in London, and offices in Paris, Berlin, Tunis, Lagos, Dubai, Cape Town and the USA. InstaDeep has been named among the Top 100 global AI startups for three consecutive years by CB Insights, as well as one of the 100 most promising B2B companies in Europe, by Sifted. We have created an environment that ensures a challenge by working closely with a broad spectrum of high-quality clients, pushing you to thrive in an environment that’s rarely tedious and always looking to push you to come up with outside-the-box solutions using cutting-edge technologies. In our mission to stay ahead of the curve, we are proud to partner with firms such as BioNTech SE, Google DeepMind, NVIDIA and Intel, and world-class universities such as MIT, Oxford, UCL, and Imperial College London. We are also an NVIDIA Elite Service Delivery Partner and Google Cloud Partner.

Are you a Research Scientist in Science? You will contribute to knowledge in different fields, and plan and conduct experiments to help expand the canon of the company's scientific knowledge.

If so then keep reading…. 

As a Research Scientist in Science, you’ll be a part of the Research department, 

The Research Scientist in Science must accomplish the following:  

• Collaborate with other researchers and experts to develop machine-learning methods for problems in computational biology.
• Engage and assist in the identification of research directions
• Contribute to the design and implementation of models, tools and libraries to accelerate our research effort.
• Adapt neural network algorithms to deploy on supercomputing architectures to best exploit modern parallel environments 
• Report and present experimental results and research findings clearly and effectively, both internally and externally, verbally and in writing. 
• Contribute to the team’s publication efforts.
• Bridge the gap between the research and product teams by integrating new fundamental research into applied projects. 

Requirements:  

• Ph.D. degree in Computer Science, Machine Learning or a related field.
• Experience using Deep Learning frameworks such as PyTorch, Tensorflow and/or Jax.
• Experience in developing and debugging in Python3 or similar languages.
• Experience with high-performance computing methods and frameworks such as MPI, Ray (distribution on clusters of CPUs and accelerators)
• Experience in planning and conducting research works
• A demonstrated ability to successfully deliver high-quality research, including publishing scientific papers (ICLR, NeurIPS, ICML, etc).
• Excellent communication skills and collaborative spirit.

Nice to haves

• 2-5 years experience

• Software engineering experience demonstrated via previous work, and contributions to open source or coding competitions.
• Reinforcement Learning, Computer Vision, or Natural Language Processing experience.

Our Diversity, Equity, and Inclusion commitments

We empower individuals to celebrate their uniqueness here at InstaDeep. Our team comes from all walks of life, and we’re proud to continue encouraging and supporting applicants from underrepresented groups across the globe. Our commitment to creating an authentic environment comes from our ability to learn and grow from our diversity, and how better to experience this by other than by joining our team? 

At present, we operate in a hybrid work model of two days mandatory a week in the office. We are continuing to review the situation with the well-being of InstaDeepers at the forefront of our minds.

Right to work: Please note you will require the legal right to work in the location you are applying for. 

If you have any further questions please do not hesitate to contact us at: talent@instadeep.com

The Team You'll Join

Your Impact

• Build and deploy ML algorithms to production that power 500+ e-commerce and marketplace sites across 40 countries, directly impacting revenue growth, operational efficiency, and transaction safety
• Tackle real-world catalog challenges including automatic content rewriting, product attribute extraction from images and text, variant detection, product categorization, seller onboarding automation, and trending product prediction
• Work with cutting-edge AI techniques including multimodal models and LLM fine-tuning—Mirakl is one of the few French players with fine-tuned LLMs in large-scale production
• Own your projects end-to-end: from data analysis and prototyping to production deployment with Data Engineers and dev teams, plus building dashboards to monitor algorithm performance
• Collaborate across teams to refine use cases, user experience, and integration paths while presenting results at weekly data science meetings

What You'll Bring to the Role

• 4+ years of experience as a Data Scientist with strong hands-on NLP and applied ML in industry
• Proven track record of deploying Machine Learning algorithms to production
• Experience with Spark development for large-scale data processing

• Expertise in NLP and Computer Vision algorithms and state-of-the-art architectures (e.g., Transformers)
• Proficiency in Python and TensorFlow and/or PyTorch
• Knowledge of the latest LLMs and fine-tuning techniques
• Data-driven, pragmatic, and business-oriented approach
• Strong ownership and autonomy with excellent team collaboration

Tech Stack

• Python, TensorFlow, PyTorch, Hugging Face

• Autotrain, Unsloth, Galileo, LangChain, Anyscale

• Databricks, Spark, AWS (Amazon Redshift, S3), SQL, Airflow, Delta Lake

Our Hiring Process

1. A 30/45-minute phone call with one of our Tech recruiters to discuss your background, expectations, and the role
2. A 30-minute technical call with someone from the Data Science team to dive into concrete aspects of your expertise and how it fits our projects
3. A take-home assignment to demonstrate your technical skills
4. A 75-minute technical debrief and discussion with the Data Science Team managers
5. 2x45mn STAR interviews with future Mirakl colleagues to discuss our values and culture

The Team You'll Join

Your Impact

• Build and deploy ML algorithms to production that power 500+ e-commerce and marketplace sites across 40 countries, directly impacting revenue growth, operational efficiency, and transaction safety
• Tackle real-world catalog challenges including automatic content rewriting, product attribute extraction from images and text, variant detection, product categorization, seller onboarding automation, and trending product prediction
• Work with cutting-edge AI techniques including multimodal models and LLM fine-tuning—Mirakl is one of the few French players with fine-tuned LLMs in large-scale production
• Own your projects end-to-end: from data analysis and prototyping to production deployment with Data Engineers and dev teams, plus building dashboards to monitor algorithm performance
• Collaborate across teams to refine use cases, user experience, and integration paths while presenting results at weekly data science meetings

What You'll Bring to the Role

• 4+ years of experience as a Data Scientist with strong hands-on NLP and applied ML in industry
• Proven track record of deploying Machine Learning algorithms to production
• Experience with Spark development for large-scale data processing

• Expertise in NLP and Computer Vision algorithms and state-of-the-art architectures (e.g., Transformers)
• Proficiency in Python and TensorFlow and/or PyTorch
• Knowledge of the latest LLMs and fine-tuning techniques
• Data-driven, pragmatic, and business-oriented approach
• Strong ownership and autonomy with excellent team collaboration

Tech Stack

• Python, TensorFlow, PyTorch, Hugging Face

• Autotrain, Unsloth, Galileo, LangChain, Anyscale

• Databricks, Spark, AWS (Amazon Redshift, S3), SQL, Airflow, Delta Lake

Our Hiring Process

1. A 30/45-minute phone call with one of our Tech recruiters to discuss your background, expectations, and the role
2. A 30-minute technical call with someone from the Data Science team to dive into concrete aspects of your expertise and how it fits our projects
3. A take-home assignment to demonstrate your technical skills
4. A 75-minute technical debrief and discussion with the Data Science Team managers
5. 2x45mn STAR interviews with future Mirakl colleagues to discuss our values and culture

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

About the job:

The eCommerce landscape is entering a new phase of profound change: Agentic Commerce, where AI-powered agents autonomously search, discover, compare, and ultimately purchase on behalf of users. This evolution is transforming how customers interact with products—how they arrive, engage, how choices are filtered, and how relevance is determined in a rapidly evolving paradigm. From product discovery to marketplace optimization, these changes are reshaping retailers’ ecosystems.

In this context, as a Senior AI Engineer, you will join our Data team (60+ people) to prototype, iterate, and integrate agentic systems into Mirakl products, working closely with Data Scientists, Data Engineers, Product Managers and Software Development teams.

The position is open for a Permanent contract (CDI) or Freelance, based in Paris or Bordeaux (4 days on site).

Our stack and tools:

Python, Tensorflow, Pytorch, Databricks, Spark, AWS, SQL, Airflow, Delta Lake

During a typical week, you will:

• Design, develop, and optimize AI agents using frameworks and tools such as LangChain, LangGraph, and LangFlow
• Leverage large language models (LLMs) and techniques such as Retrieval-Augmented Generation (RAG) 
• Own the full lifecycle from initial design through MVP delivery and successive iterations
• Implement reusable frameworks & tool to accelerate development while ensuring scalability (evaluation, monitoring, testing, deployment)
• Explore emerging AI paradigms, evaluate new tools and technologies, and maintain active technology watch

You'll Love This Job If you have 

• You have a minimum of 5 years of experience as a Data Scientist or Machine Learning Engineer with a strong Software Engineering skills
• Proven experience building AI agents using LLMs, RAG, MCP and related technologies with architectural design experience
• Production deployment expertise - you've shipped AI solutions in production
• Strong proficiency in Python
• Curiosity and continuous learning - you stay current with AI/ML trends and love exploring new technologies
• Strong communication skills in both English and French

Feel free to add a link to your GitHub in your CV so we can understand what you have worked on!

Want to join us? Here is our process 

• A 30-minute phone conversation with one of our Tech recruiters. This will be an opportunity to discuss your background, expectations, and discover what Mirakl can offer you in return.
• An initial 30-minute technical discussion via Zoom with a member of the Data Science team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
• A 90-minute technical review and discussion with a manager from the Data Science team
• 2 x 45-minute "STAR" Zoom interviews with future Mirakl colleagues to discuss our values and company culture.

About the job:

The eCommerce landscape is entering a new phase of profound change: Agentic Commerce, where AI-powered agents autonomously search, discover, compare, and ultimately purchase on behalf of users. This evolution is transforming how customers interact with products—how they arrive, engage, how choices are filtered, and how relevance is determined in a rapidly evolving paradigm. From product discovery to marketplace optimization, these changes are reshaping retailers’ ecosystems.

In this context, as a Senior AI Engineer, you will join our Data team (60+ people) to prototype, iterate, and integrate agentic systems into Mirakl products, working closely with Data Scientists, Data Engineers, Product Managers and Software Development teams.

The position is open for a Permanent contract (CDI) or Freelance, based in Paris or Bordeaux 4 days on site.

Our stack and tools:

Python, Tensorflow, Pytorch, Databricks, Spark, AWS, SQL, Airflow, Delta Lake

During a typical week, you will:

• Design, develop, and optimize AI agents using frameworks and tools such as LangChain, LangGraph, and LangFlow
• Leverage large language models (LLMs) and techniques such as Retrieval-Augmented Generation (RAG) 
• Own the full lifecycle from initial design through MVP delivery and successive iterations
• Implement reusable frameworks & tool to accelerate development while ensuring scalability (evaluation, monitoring, testing, deployment)
• Explore emerging AI paradigms, evaluate new tools and technologies, and maintain active technology watch

You'll Love This Job If you have 

• You have a minimum of 5 years of experience as a Data Scientist or Machine Learning Engineer with a strong Software Engineering skills
• Proven experience building AI agents using LLMs, RAG, MCP and related technologies with architectural design experience
• Production deployment expertise - you've shipped AI solutions in production
• Strong proficiency in Python
• Curiosity and continuous learning - you stay current with AI/ML trends and love exploring new technologies
• Strong communication skills in both English and French

Feel free to add a link to your GitHub in your CV so we can understand what you have worked on!

Want to join us? Here is our process 

• A 30-minute phone conversation with one of our Tech recruiters. This will be an opportunity to discuss your background, expectations, and discover what Mirakl can offer you in return.
• An initial 30-minute technical discussion via Zoom with a member of the Data Science team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
• A 90-minute technical review and discussion with a manager from the Data Science team
• 2 x 45-minute "STAR" Zoom interviews with future Mirakl colleagues to discuss our values and company culture.

Who We Are

Headquartered in New York City, Take-Two Interactive Software, Inc. is a leading developer, publisher, and marketer of interactive entertainment for consumers around the globe. We develop and publish products principally through Rockstar Games, 2K, and Zynga. Our strategy is to create hit entertainment experiences, delivered on every platform relevant to our audience through a variety of sound business models. Our pillars - creativity, innovation, and efficiency - guide us as we strive to create the highest quality, most captivating experiences for our consumers. The Company’s common stock is publicly traded on NASDAQ under the symbol TTWO. For more corporate and product information please visit our website at http://www.take2games.com.

The Challenge

Created in 2010 and acquired by Take-two Interactive in 2021, Dynamixyz specializes in high quality 3D facial animation and content creation. Dynamixyz powers the facial animation technology behind 2K and Rockstars labels’ titles such as NBA 2K games, Red Dead Redemption 2 and GTAV. We are looking for our next team mate to jump on-board the Performer software development team and assist in developing our facial animation hub as server-based platform. 

As a Senior Software Engineer, you will be the bridge between complex system logic and a seamless user experience. You will contribute to our team's success by developing high-performance software and intuitive interfaces that solve real-world technical challenges.

What You’ll Take On

• Design, build, and maintain robust applications using C++ and Python to meet high-performance standards.
• Lead the development of frontend interfaces using the Qt framework, ensuring a responsive and user-friendly experience.
• Implement and optimize communication protocols such as gRPC and REST-API for seamless internal and external data flow.
• Navigate and manage Windows-based and Linux-based systems to ensure stable application deployment and debugging.
• Own the CI/CD pipeline and Git workflows to achieve a 99% build success rate and rapid deployment cycles.
• Actively drive Sprint goals and maintain high-quality documentation within Jira and Confluence.

What You Bring 

• 5+ years experience in C++ and Python development within a professional environment.
• A strong portfolio or history of developing desktop applications using the Qt framework.
• Deep familiarity with Linux environments, including shell scripting and system-level troubleshooting.
• Mastery of Git for version control and a clear understanding of CI/CD principles.
• Practical experience working within Agile/Scrum teams and utilizing tools like Jira and Confluence to track progress.
• Hands-on experience implementing gRPC and REST-API.
• Extensive experience with Node.js, Go, or Python in a multi-tenant environment, specifically managing large binary blobs (point clouds/video).
• Experience with FFmpeg, WebRTC, or specialized media servers to handle live video streams for facial analysis.
• Ability to manage "compute-heavy" workloads, shifting facial solve tasks between the user's device (Edge) and the Cloud.
• Deep understanding of linear blend skinning and how facial rigs transition between expressions, ideally with a focus on Blendshapes & Morph Targets
• Familiarity with OpenCV or TensorFlow/PyTorch for detecting facial landmarks (eyes, lips, brows).
• Understanding of edge loops and mesh density required for realistic facial deformation.

Great to Have

• Experience with Docker or Kubernetes within a Linux ecosystem.
• Experience conducting peer code reviews and onboarding new team members.
• Great team spirit 

What We Offer You

• Great Company Culture. Ranked as one of the most creative and innovative places to work, creativity, innovation, efficiency, diversity and philanthropy are among the core tenets of our organization and are integral drivers of our continued success.
• Growth. As a global entertainment company, we pride ourselves on creating environments where employees are encouraged to be themselves, inquisitive, collaborative and to grow within and around the company.
• Work Hard, Play Hard. Our employees bond, blow-off steam, and flex some creative muscles – through corporate boot camp classes, company parties, game release events, monthly socials, and team challenges.
• Benefits. Include, but aren't limited to: healthcare insurance for high-quality medical and dental care that covers hospitalization, optical care, alternative medicine, and flu vaccines; Per Obligatoire pension plan; 50% reimbursement for public transport commuting; company-funded meal vouchers; 540 € annual fitness reimbursement; 24/7 mental wellbeing support; an Employee Stock Purchase Plan with 15% discount; charitable donation matching and volunteer leave; 25 days of annual leave and extra company holidays, Reduction of Working Time (RTT), and Repos Forfait Jours (RFJ).

Please be aware that Take-Two does not conduct job interviews or make job offers over third-party messaging apps such as Telegram, WhatsApp, or others. Take-Two also does not engage in any financial exchanges during the recruitment or onboarding process, and the Company will never ask a candidate for their personal or financial information over an app or other unofficial chat channel. Any attempt to do so may be the result of a scam or phishing exercise. Take-Two’s in-house recruitment team will only contact individuals through their official Company email addresses (i.e., via a take2games.com email domain). If you need to report an issue or otherwise have questions, please contact Careers@take2games.com

As an equal opportunity employer, Take-Two Interactive Software, Inc. (“Take-Two”) is committed to fostering and celebrating the diverse thoughts, cultures, and backgrounds of its talent, partners, and communities throughout its organization. Consistent with this commitment, Take-Two does not discriminate or retaliate against any employee or job applicant because of their race, color, religion, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, and genetic information (including family medical history), or on the basis of any other trait protected by applicable law. If you need to report a concern or have questions regarding Take-Two’s equal opportunity commitment, please contact Careers@take2games.com.

#LI-Hybrid

#LI-PH1

About the job:

The eCommerce landscape is entering a new phase of profound change: Agentic Commerce, where AI-powered agents autonomously search, discover, compare, and ultimately purchase on behalf of users. This evolution is transforming how customers interact with products—how they arrive, engage, how choices are filtered, and how relevance is determined in a rapidly evolving paradigm. From product discovery to marketplace optimization, these changes are reshaping retailers’ ecosystems.

In this context, as a Senior AI Engineer, you will join our Data team (60+ people) to prototype, iterate, and integrate agentic systems into Mirakl products, working closely with Data Scientists, Data Engineers, Product Managers and Software Development teams.

The position is open for a Permanent contract (CDI) based in Paris or Bordeaux with :

- 4 days onsite per week 

- 1 day worked remotely per week

Our stack and tools:

Python, Tensorflow, Pytorch, Databricks, Spark, AWS, SQL, Airflow, Delta Lake

During a typical week, you will:

• Design, develop, and optimize AI agents using frameworks and tools such as LangChain, LangGraph, and LangFlow
• Leverage large language models (LLMs) and techniques such as Retrieval-Augmented Generation (RAG) 
• Own the full lifecycle from initial design through MVP delivery and successive iterations
• Implement reusable frameworks & tool to accelerate development while ensuring scalability (evaluation, monitoring, testing, deployment)
• Explore emerging AI paradigms, evaluate new tools and technologies, and maintain active technology watch

You'll Love This Job If you have 

• You have a minimum of 5 years of experience as a Data Scientist or Machine Learning Engineer with a strong Software Engineering skills
• Proven experience building AI agents using LLMs, RAG, MCP and related technologies with architectural design experience
• Production deployment expertise - you've shipped AI solutions in production
• Strong proficiency in Python
• Curiosity and continuous learning - you stay current with AI/ML trends and love exploring new technologies
• Strong communication skills in both English and French

Feel free to add a link to your GitHub in your CV so we can understand what you have worked on!

Want to join us? Here is our process 

• A 30-minute phone conversation with one of our Tech recruiters. This will be an opportunity to discuss your background, expectations, and discover what Mirakl can offer you in return.
• An initial 30-minute technical discussion via Zoom with a member of the Data Science team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
• A 90-minute technical review and discussion with a manager from the Data Science team
• 2 x 45-minute "STAR" Zoom interviews with future Mirakl colleagues to discuss our values and company culture.

About the job:

The eCommerce landscape is entering a new phase of profound change: Agentic Commerce, where AI-powered agents autonomously search, discover, compare, and ultimately purchase on behalf of users. This evolution is transforming how customers interact with products—how they arrive, engage, how choices are filtered, and how relevance is determined in a rapidly evolving paradigm. From product discovery to marketplace optimization, these changes are reshaping retailers’ ecosystems.

In this context, as a Senior AI Engineer, you will join our Data team (60+ people) to prototype, iterate, and integrate agentic systems into Mirakl products, working closely with Data Scientists, Data Engineers, Product Managers and Software Development teams.

The position is open for a Permanent contract (CDI), based in Paris or Bordeaux with :

- 4 days onsite per week 

- 1 day worked remotely per week

Our stack and tools:

Python, Tensorflow, Pytorch, Databricks, Spark, AWS, SQL, Airflow, Delta Lake

During a typical week, you will:

• Design, develop, and optimize AI agents using frameworks and tools such as LangChain, LangGraph, and LangFlow
• Leverage large language models (LLMs) and techniques such as Retrieval-Augmented Generation (RAG) 
• Own the full lifecycle from initial design through MVP delivery and successive iterations
• Implement reusable frameworks & tool to accelerate development while ensuring scalability (evaluation, monitoring, testing, deployment)
• Explore emerging AI paradigms, evaluate new tools and technologies, and maintain active technology watch

You'll Love This Job If you have 

• You have a minimum of 5 years of experience as a Data Scientist or Machine Learning Engineer with a strong Software Engineering skills
• Proven experience building AI agents using LLMs, RAG, MCP and related technologies with architectural design experience
• Production deployment expertise - you've shipped AI solutions in production
• Strong proficiency in Python
• Curiosity and continuous learning - you stay current with AI/ML trends and love exploring new technologies
• Strong communication skills in both English and French

Feel free to add a link to your GitHub in your CV so we can understand what you have worked on!

Want to join us? Here is our process 

• A 30-minute phone conversation with one of our Tech recruiters. This will be an opportunity to discuss your background, expectations, and discover what Mirakl can offer you in return.
• An initial 30-minute technical discussion via Zoom with a member of the Data Science team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
• A 90-minute technical review and discussion with a manager from the Data Science team
• 2 x 45-minute "STAR" Zoom interviews with future Mirakl colleagues to discuss our values and company culture.

About the job

As part of our Data team (60+ people), your main mission will be to prototype, iterate, and put algorithms into production in collaboration with the Product teams, Data Engineers, and Development teams.

The topics you will be working on will have a real impact on 450+ of the world's largest retailers (Best Buy, Decathlon, Leroy Merlin, Macy's, etc.) and 100k+ sellers. The goal is to make the most of our rich and varied data in order to increase their revenue, optimize the operational management of their businesses, and ensure the security of users and transactions. 

We are looking for someone on a permanent contract, based in Paris or Bordeaux (1 day remote per week).

Here are some of the current and future topics the team is working on:

• Detecting anomalies in product prices
• Analyzing sentiment in seller/consumer exchanges to prioritize critical messages
• Estimating package delivery times
• Predicting and anticipating stock shortages
• Detecting anomalies in seller behavior
• Developing AI agents to help sellers take action on their businesses
  
  

This job offers you:

• Implementing algorithms that will have a visible impact on more than 500 e-commerce sites/marketplaces in 40 countries, some of which are very large (millions of products, customers, orders per year)
• A wide variety of techniques (time series, heuristics, deep learning, NLP, LLM, etc.).
• Real autonomy and responsibility in the projects you own
  
  

Our stack and tools:
Python, Tensorflow, Keras, Pytorch, Databricks, Spark, AWS (Amazon Redshift, s3, etc.), SQL, Airflow, Delta Lake

On a daily basis, you will:

• Analyze and prepare data, prototype algorithms
• Put them into production in collaboration with Data Engineers and development teams
• Create dashboards to illustrate the relevance of algorithms and monitor production
• Present results at weekly data science meetings and participate in team brainstorming sessions
• Liaise with other teams to refine use cases, user experience, and integration methods

You will enjoy this job if:

• You have a background in machine learning, mathematics, computer science (or a related field)
• You already have 6-8 years of experience in a similar position
• You have significant experience in applied ML in a business setting
• You have a good knowledge of machine learning and deep learning algorithms (particularly state-of-the-art architectures, such as Transformers)
• You are proficient in Python, Tensorflow, and/or PyTorch.
• You are pragmatic, data-driven, and business-oriented with good team spirit.
• You like to take ownership of your projects and are curious.
• You have a positive attitude: respect and kindness are part of your values.

Want to join us? ⭐

• A 30-minute phone call with one of our Tech recruiters. This will be an opportunity to discuss your background and expectations, and to find out what Mirakl can offer you in return.
• An initial 30-minute technical discussion via Zoom with a member of the Data Science team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
• A practical case study to complete at home.
• A 75-minute technical review and discussion with a manager from the Data Science team.
• A final 1-hour Zoom meeting with future Mirakl colleagues to discuss our values and corporate culture. 

About the job

As part of our Data team (60+ people), your main mission will be to prototype, iterate, and put algorithms into production in collaboration with the Product teams, Data Engineers, and Development teams.

The topics you will be working on will have a real impact on 450+ of the world's largest retailers (Best Buy, Decathlon, Leroy Merlin, Macy's, etc.) and 100k+ sellers. The goal is to make the most of our rich and varied data in order to increase their revenue, optimize the operational management of their businesses, and ensure the security of users and transactions. 

We are looking for someone on a permanent contract, based in Paris or Bordeaux (1 day remote per week).

Here are some of the current and future topics the team is working on:

• Detecting anomalies in product prices
• Analyzing sentiment in seller/consumer exchanges to prioritize critical messages
• Estimating package delivery times
• Predicting and anticipating stock shortages
• Detecting anomalies in seller behavior
• Developing AI agents to help sellers take action on their businesses
  
  

This job offers you:

• Implementing algorithms that will have a visible impact on more than 500 e-commerce sites/marketplaces in 40 countries, some of which are very large (millions of products, customers, orders per year)
• A wide variety of techniques (time series, heuristics, deep learning, NLP, LLM, etc.).
• Real autonomy and responsibility in the projects you own
  
  

Our stack and tools:
Python, Tensorflow, Keras, Pytorch, Databricks, Spark, AWS (Amazon Redshift, s3, etc.), SQL, Airflow, Delta Lake

On a daily basis, you will:

• Analyze and prepare data, prototype algorithms
• Put them into production in collaboration with Data Engineers and development teams
• Create dashboards to illustrate the relevance of algorithms and monitor production
• Present results at weekly data science meetings and participate in team brainstorming sessions
• Liaise with other teams to refine use cases, user experience, and integration methods

You will enjoy this job if:

• You have a background in machine learning, mathematics, computer science (or a related field)
• You already have 6-8 years of experience in a similar position
• You have significant experience in applied ML in a business setting
• You have a good knowledge of machine learning and deep learning algorithms (particularly state-of-the-art architectures, such as Transformers)
• You are proficient in Python, Tensorflow, and/or PyTorch.
• You are pragmatic, data-driven, and business-oriented with good team spirit.
• You like to take ownership of your projects and are curious.
• You have a positive attitude: respect and kindness are part of your values.

Want to join us? ⭐

• A 30-minute phone call with one of our Tech recruiters. This will be an opportunity to discuss your background and expectations, and to find out what Mirakl can offer you in return.
• An initial 30-minute technical discussion via Zoom with a member of the Data Science team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
• A practical case study to complete at home.
• A 75-minute technical review and discussion with a manager from the Data Science team.
• A final 1-hour Zoom meeting with future Mirakl colleagues to discuss our values and corporate culture. 

About the job

As part of our Data team (60+ people), your main mission will be to prototype, iterate, and put algorithms into production in collaboration with the Product teams, Data Engineers, and Development teams.

The topics you will be working on will have a real impact on 450+ of the world's largest retailers (Best Buy, Decathlon, Leroy Merlin, Macy's, etc.) and 100k+ sellers. The goal is to make the most of our rich and varied data in order to increase their revenue, optimize the operational management of their businesses, and ensure the security of users and transactions. 

We are looking for someone on a permanent contract, based in Paris or Bordeaux (1 day remote per week).

Here are some of the current and future topics the team is working on:

• Detecting anomalies in product prices
• Analyzing sentiment in seller/consumer exchanges to prioritize critical messages
• Estimating package delivery times
• Predicting and anticipating stock shortages
• Detecting anomalies in seller behavior
• Developing AI agents to help sellers take action on their businesses
  
  

This job offers you:

• Implementing algorithms that will have a visible impact on more than 500 e-commerce sites/marketplaces in 40 countries, some of which are very large (millions of products, customers, orders per year)
• A wide variety of techniques (time series, heuristics, deep learning, NLP, LLM, etc.).
• Real autonomy and responsibility in the projects you own
  
  

Our stack and tools:
Python, Tensorflow, Keras, Pytorch, Databricks, Spark, AWS (Amazon Redshift, s3, etc.), SQL, Airflow, Delta Lake

On a daily basis, you will:

• Analyze and prepare data, prototype algorithms
• Put them into production in collaboration with Data Engineers and development teams
• Create dashboards to illustrate the relevance of algorithms and monitor production
• Present results at weekly data science meetings and participate in team brainstorming sessions
• Liaise with other teams to refine use cases, user experience, and integration methods

You will enjoy this job if:

• You have a background in machine learning, mathematics, computer science (or a related field)
• You already have 3 years of experience in a similar position
• You have significant experience in applied ML in a business setting
• You have a good knowledge of machine learning and deep learning algorithms (particularly state-of-the-art architectures, such as Transformers)
• You are proficient in Python, Tensorflow, and/or PyTorch.
• You are pragmatic, data-driven, and business-oriented with good team spirit.
• You like to take ownership of your projects and are curious.
• You have a positive attitude: respect and kindness are part of your values.

Want to join us? ⭐

• A 30-minute phone call with one of our Tech recruiters. This will be an opportunity to discuss your background and expectations, and to find out what Mirakl can offer you in return.
• An initial 30-minute technical discussion via Zoom with a member of the Data Science team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
• A practical case study to complete at home.
• A 75-minute technical review and discussion with a manager from the Data Science team.
• A final 1-hour Zoom meeting with future Mirakl colleagues to discuss our values and corporate culture. 

About the job

As part of our Data team (60+ people), your main mission will be to prototype, iterate, and put algorithms into production in collaboration with the Product teams, Data Engineers, and Development teams.

The topics you will be working on will have a real impact on 450+ of the world's largest retailers (Best Buy, Decathlon, Leroy Merlin, Macy's, etc.) and 100k+ sellers. The goal is to make the most of our rich and varied data in order to increase their revenue, optimize the operational management of their businesses, and ensure the security of users and transactions. 

We are looking for someone on a permanent contract, based in Paris or Bordeaux (1 day remote per week).

Here are some of the current and future topics the team is working on:

• Detecting anomalies in product prices
• Analyzing sentiment in seller/consumer exchanges to prioritize critical messages
• Estimating package delivery times
• Predicting and anticipating stock shortages
• Detecting anomalies in seller behavior
• Developing AI agents to help sellers take action on their businesses
  
  

This job offers you:

• Implementing algorithms that will have a visible impact on more than 500 e-commerce sites/marketplaces in 40 countries, some of which are very large (millions of products, customers, orders per year)
• A wide variety of techniques (time series, heuristics, deep learning, NLP, LLM, etc.).
• Real autonomy and responsibility in the projects you own
  
  

Our stack and tools:
Python, Tensorflow, Keras, Pytorch, Databricks, Spark, AWS (Amazon Redshift, s3, etc.), SQL, Airflow, Delta Lake

On a daily basis, you will:

• Analyze and prepare data, prototype algorithms
• Put them into production in collaboration with Data Engineers and development teams
• Create dashboards to illustrate the relevance of algorithms and monitor production
• Present results at weekly data science meetings and participate in team brainstorming sessions
• Liaise with other teams to refine use cases, user experience, and integration methods

You will enjoy this job if:

• You have a background in machine learning, mathematics, computer science (or a related field)
• You already have 3 years of experience in a similar position
• You have significant experience in applied ML in a business setting
• You have a good knowledge of machine learning and deep learning algorithms (particularly state-of-the-art architectures, such as Transformers)
• You are proficient in Python, Tensorflow, and/or PyTorch.
• You are pragmatic, data-driven, and business-oriented with good team spirit.
• You like to take ownership of your projects and are curious.
• You have a positive attitude: respect and kindness are part of your values.

Want to join us? ⭐

• A 30-minute phone call with one of our Tech recruiters. This will be an opportunity to discuss your background and expectations, and to find out what Mirakl can offer you in return.
• An initial 30-minute technical discussion via Zoom with a member of the Data Science team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
• A practical case study to complete at home.
• A 75-minute technical review and discussion with a manager from the Data Science team.
• A final 1-hour Zoom meeting with future Mirakl colleagues to discuss our values and corporate culture. 

About the job

As part of our Data team (60+ people), your main mission will be to prototype, iterate, and put algorithms into production in collaboration with the Product teams, Data Engineers, and Development teams.

The topics you will be working on will have a real impact on 450+ of the world's largest retailers (Best Buy, Decathlon, Leroy Merlin, Macy's, etc.) and 100k+ sellers. The goal is to make the most of our rich and varied data in order to increase their revenue, optimize the operational management of their businesses, and ensure the security of users and transactions. 

We are looking for someone on a permanent contract, based in Paris or Bordeaux (1 day remote per week).

Here are some of the current and future topics the team is working on:

• Detecting anomalies in product prices
• Analyzing sentiment in seller/consumer exchanges to prioritize critical messages
• Estimating package delivery times
• Predicting and anticipating stock shortages
• Detecting anomalies in seller behavior
• Developing AI agents to help sellers take action on their businesses
  
  

This job offers you:

• Implementing algorithms that will have a visible impact on more than 500 e-commerce sites/marketplaces in 40 countries, some of which are very large (millions of products, customers, orders per year)
• A wide variety of techniques (time series, heuristics, deep learning, NLP, LLM, etc.).
• Real autonomy and responsibility in the projects you own
  
  

Our stack and tools:
Python, Tensorflow, Keras, Pytorch, Databricks, Spark, AWS (Amazon Redshift, s3, etc.), SQL, Airflow, Delta Lake

On a daily basis, you will:

• Analyze and prepare data, prototype algorithms
• Put them into production in collaboration with Data Engineers and development teams
• Create dashboards to illustrate the relevance of algorithms and monitor production
• Present results at weekly data science meetings and participate in team brainstorming sessions
• Liaise with other teams to refine use cases, user experience, and integration methods

You will enjoy this job if:

• You have a background in machine learning, mathematics, computer science (or a related field)
• You already have 3 to 6 years of experience in a similar position
• You have significant experience in applied ML in a business setting
• You have a good knowledge of machine learning and deep learning algorithms (particularly state-of-the-art architectures, such as Transformers)
• You are proficient in Python, Tensorflow, and/or PyTorch.
• You are pragmatic, data-driven, and business-oriented with good team spirit.
• You like to take ownership of your projects and are curious.
• You have a positive attitude: respect and kindness are part of your values.

Want to join us? ⭐

• A 30-minute phone call with one of our Tech recruiters. This will be an opportunity to discuss your background and expectations, and to find out what Mirakl can offer you in return.
• An initial 30-minute technical discussion via Zoom with a member of the Data Science team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
• A practical case study to complete at home.
• A 75-minute technical review and discussion with a manager from the Data Science team.
• A final 1-hour Zoom meeting with future Mirakl colleagues to discuss our values and corporate culture. 

About the job

As part of our Data team (60+ people), your main mission will be to prototype, iterate, and put algorithms into production in collaboration with the Product teams, Data Engineers, and Development teams.

The topics you will be working on will have a real impact on 450+ of the world's largest retailers (Best Buy, Decathlon, Leroy Merlin, Macy's, etc.) and 100k+ sellers. The goal is to make the most of our rich and varied data in order to increase their revenue, optimize the operational management of their businesses, and ensure the security of users and transactions. 

We are looking for someone on a permanent contract, based in Paris or Bordeaux (1 day remote per week).

Here are some of the current and future topics the team is working on:

• Detecting anomalies in product prices
• Analyzing sentiment in seller/consumer exchanges to prioritize critical messages
• Estimating package delivery times
• Predicting and anticipating stock shortages
• Detecting anomalies in seller behavior
• Developing AI agents to help sellers take action on their businesses
  
  

This job offers you:

• Implementing algorithms that will have a visible impact on more than 500 e-commerce sites/marketplaces in 40 countries, some of which are very large (millions of products, customers, orders per year)
• A wide variety of techniques (time series, heuristics, deep learning, NLP, LLM, etc.).
• Real autonomy and responsibility in the projects you own
  
  

Our stack and tools:
Python, Tensorflow, Keras, Pytorch, Databricks, Spark, AWS (Amazon Redshift, s3, etc.), SQL, Airflow, Delta Lake

On a daily basis, you will:

• Analyze and prepare data, prototype algorithms
• Put them into production in collaboration with Data Engineers and development teams
• Create dashboards to illustrate the relevance of algorithms and monitor production
• Present results at weekly data science meetings and participate in team brainstorming sessions
• Liaise with other teams to refine use cases, user experience, and integration methods

You will enjoy this job if:

• You have a background in machine learning, mathematics, computer science (or a related field)
• You already have 3 to 6 years of experience in a similar position
• You have significant experience in applied ML in a business setting
• You have a good knowledge of machine learning and deep learning algorithms (particularly state-of-the-art architectures, such as Transformers)
• You are proficient in Python, Tensorflow, and/or PyTorch.
• You are pragmatic, data-driven, and business-oriented with good team spirit.
• You like to take ownership of your projects and are curious.
• You have a positive attitude: respect and kindness are part of your values.

Want to join us? ⭐

• A 30-minute phone call with one of our Tech recruiters. This will be an opportunity to discuss your background and expectations, and to find out what Mirakl can offer you in return.
• An initial 30-minute technical discussion via Zoom with a member of the Data Science team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
• A practical case study to complete at home.
• A 75-minute technical review and discussion with a manager from the Data Science team.
• A final 1-hour Zoom meeting with future Mirakl colleagues to discuss our values and corporate culture. 

What you’ll do

We are looking for a Senior Staff Machine Learning Engineer to join the Clinical team in the AI and Machine Learning Department. You'll lead the technical direction of AI systems that enhance clinical decision-making and patient care. You'll tackle the hardest problems in healthcare AI, from building voice-powered consultation assistants to establishing LLM evaluation frameworks that ensure clinical safety and efficacy. This role combines deep R&D with strategic technical leadership, shaping how Doctolib deploys AI in regulated healthcare environments.

Your responsibilities include but are not limited to:

Technical Strategy & Architecture

• Own the long-term technical roadmap for clinical ML systems, from model architecture selection to production deployment patterns
• Drive strategic build vs. buy decisions, balancing custom development with foundation model APIs
• Define standards for safe rollout in healthcare contexts: shadow testing, staged deployment, and human-in-the-loop workflows

End-to-End ML Delivery

• Lead design and implementation of LLM-powered clinical agents (consultation summarization, clinical coding, evidence-grounded recommendations)
• Establish rigorous evaluation frameworks using real-world clinical datasets, ensuring outputs meet clinical accuracy and safety standards
• Build production infrastructure: model and prompt versioning, guardrails, uncertainty quantification, cost optimization, and observability
• Define a bold strategy for online and offline performance objectives to reach new levels of healthcare professionals satisfaction

Leadership & Impact

• Mentor Staff or Senior ML Engineers and Applied Scientists, elevating technical standards across the organization
• Lead cross-functional initiatives spanning Product, Medical Affairs, Legal, and Compliance teams
• Translate clinical needs into research questions and production systems that measurably improve patient outcomes
• Partner with our medical, legal, and compliance teams to meet EU regulatory expectations (e.g., GDPR, MDR, upcoming EU AI Act) and market standards.

Who you are

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 have 10+ years in ML/AI with 3+ years at Staff+ or Principal level leading complex, multi-team technical initiatives
• You have a PhD in Computer Science, AI, Statistics, or related field (or equivalent research experience)
• You have deep expertise in at least two of: clinical NLP, LLM fine-tuning and evaluation, automatic speech recognition, RAG systems, or reinforcement learning
• You are expert in Python, PyTorch/Transformers for training, vLLM/similar for inference with a track record deploying ML systems in production (AWS/GCP)
• You have exceptional communication skills and are able to align diverse stakeholders and explain complex technical decisions

Now it would be fantastic if you have:

• Publications in top-tier ML/AI conferences (NeurIPS, ICLR, ACL) or medical informatics venues
• Experience with EU healthcare regulations (GDPR, MDR, AI Act)
• Prior work with clinical data or healthcare applications

What we offer

• Free comprehensive 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 abroad 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
• Hiring Manager Interview
• Behavioral Interview
• Technical Questions 
• Technical Case Study
• At least one reference check

Job details

• Permanent position
• Full-time
• Hybrid work mode (3 days/week in the office)
• Paris, France
• Start date: as soon as possible

If you would like to find out more about tech life at Doctolib, feel free to read our latest Medium blog articles!

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, 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!

All information provided is processed by Doctolib for application management. For data processing details, click here.

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.