Skip to content
Backend Engineer

Backend Engineer

Technical Lead - GPU Infrastructure

Jobgether

Удалённо

Откликнуться на сайте работодателя

Описание вакансии

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Technical Lead - GPU Infrastructure based in Switzerland.
This is a hands-on technical leadership role responsible for architecting and delivering a large-scale GPU infrastructure platform.

You will lead the evolution from managed Kubernetes workloads toward bare-metal GPU infrastructure, including Slurm-based research computing and Kubernetes-powered inference.

The role combines deep systems expertise with engineering leadership, team management, and direct ownership of architecture and delivery.

You will oversee a distributed team spanning backend, frontend, DevOps, QA, and documentation while maintaining high technical standards.

Your work will support research, model training, and managed inference workloads requiring reliable, scalable, and observable GPU compute.

You will also serve as the primary technical interface with infrastructure partners, hardware providers, and internal platform consumers.

This is an opportunity to shape the architecture and operational foundations of a sophisticated GPU platform in a fully remote environment.

Accountabilities
The Technical Lead will own the platform architecture and engineering delivery while remaining deeply involved in technical decisions, infrastructure operations, team leadership, and partner relationships.

  • Own the end-to-end platform architecture, including architecture proposals, high-level and low-level designs, technical reviews, and ongoing architecture documentation.
  • Lead and line-manage a distributed engineering team across backend, frontend, DevOps, QA, and documentation.
  • Establish engineering standards, oversee code and design reviews, manage release gates, conduct one-to-ones, and provide growth and performance feedback.
  • Design, build, and operate a managed Slurm service supporting research and model-training workloads.
  • Own Slurm controllers, accounting, partitions, login nodes, node onboarding, acceptance testing, driver and CUDA baselines, upgrades, stalled-job detection, node health, draining, autohealing, storage visibility, identity, and workload isolation.
  • Lead GPU infrastructure operations on bare-metal environments, including NVIDIA drivers, CUDA, Fabric Manager, NVSwitch, DCGM, MIG, node burn-in, and acceptance processes.
  • Own Kubernetes cluster bootstrap and lifecycle on partner-provided bare metal, including NVIDIA GPU Operator and Network Operator.
  • Oversee GPU isolation using technologies such as KubeVirt and VFIO and manage day-two infrastructure operations, upgrades, backup, recovery, and node replacement.
  • Define managed inference architecture covering serving, multi-GPU and multi-node parallelism, autoscaling, request routing, endpoint reliability, and confidential-compute capabilities.
  • Establish observability across the control plane, GPU fleet, and application layers through metrics, logging, alerting, and SLOs.
  • Lead incident response, post-incident reviews, and the development of an on-call model that is sustainable for a lean engineering organization.
  • Act as the primary technical interface with infrastructure partners and vendors, translating requirements into written specifications and acceptance tests.
  • Manage technical escalations with partners through resolution and contribute to capacity planning and hardware sourcing decisions.
  • Work directly with research, model-training, and product teams to translate workloads into platform requirements and manage capacity constraints.
  • Hire and develop members of the platform team while maintaining a high technical bar.
  • Contribute to architecture decisions involving distributed systems, high-performance computing, networking, storage, virtualization, and GPU workloads.

Requirements
The ideal candidate combines deep hands-on GPU and infrastructure expertise with proven technical leadership experience. They should be comfortable operating complex production systems, making architecture decisions, leading distributed teams, and remaining close to the code and infrastructure.

  • 8+ years of hands-on engineering experience, including at least 3 years leading teams responsible for infrastructure platforms used by other teams.
  • Bachelor's or Master's degree in computer science, engineering, or a related field, or equivalent practical experience.
  • Extensive hands-on experience operating Slurm in production, including slurmctld, slurmdbd, partitions, QoS, priority, accounting, prolog and epilog, node health, and upgrades.
  • Experience operating HPC or GPU training clusters for research or model-development users.
  • Strong experience operating NVIDIA GPU fleets on bare metal, including driver and CUDA lifecycles, Fabric Manager, NVSwitch, DCGM, MIG, node burn-in, and acceptance.
  • Deep knowledge of InfiniBand, subnet configuration, RDMA, SR-IOV, and diagnosing multi-node NCCL performance issues.
  • Strong Linux systems expertise, including kernel modules, drivers, PCIe passthrough, vfio-pci, cgroups, namespaces, and performance tuning.
  • Proven production Kubernetes experience covering control planes, upgrades, CNI, CSI, operators, custom controllers, and multi-tenancy.
  • Experience with HPC storage and large-scale data movement, including shared filesystems such as VAST, Lustre, or NFS and node-local NVMe caching.
  • Experience distributing large model weights and datasets across multiple nodes.
  • Strong observability and operations experience with Prometheus, Grafana, Loki, or comparable platforms, including SLOs, incident response, and post-incident reviews.
  • Working proficiency in JavaScript and Node.js sufficient to review control-plane, CLI, and worker services and make architecture decisions.
  • Experience delivering a multi-tenant IaaS, PaaS, research computing service, or comparable platform with resource isolation, quotas, usage metering, APIs, and CLI interfaces.
  • Demonstrated people leadership across time zones and the ability to lead cross-functional technical reviews.
  • Strong written architecture and decision-making skills, including documenting alternatives and trade-offs.
  • Confidence communicating technical decisions and respectfully challenging partners or executives when necessary.
  • Excellent written and spoken English.
  • Fully remote availability with a working location between UTC and UTC+5:30 to provide overlap with teams and partners across Europe and India.
  • Willingness to travel occasionally to partner sites and team events.

Desirable Experience Includes

  • Slurm operators on Kubernetes, such as Soperator or Slinky, or Kubernetes-native schedulers such as Kueue, Volcano, KAI, or Kubeflow Trainer.
  • Modern model-serving technologies such as vLLM, SGLang, or TensorRT-LLM.
  • GPU parallelism strategies, quantization trade-offs, and GPU memory planning.
  • Multi-tenant GPU isolation using KubeVirt, Kata Containers, QEMU/KVM, Firecracker, or similar technologies.
  • Confidential computing technologies such as Intel TDX, AMD SEV-SNP, or NVIDIA confidential-compute capabilities.
  • Cluster API, kubeadm, Cilium, GPU autohealing, infrastructure as code, and GitOps.
  • Experience working on the operator side of a GPU cloud, university or national HPC center, or AI research platform.
  • Peer-to-peer or distributed-systems experience.
  • Experience working with hardware providers responsible for provisioning but not operating infrastructure, including establishing contracts and acceptance tests.

Benefits

  • 100% remote position.
  • Opportunity to lead the architecture and delivery of a sophisticated GPU infrastructure platform.
  • High-impact technical leadership role spanning bare-metal GPU infrastructure, Slurm, Kubernetes, inference, and observability.
  • Leadership responsibility for a distributed engineering organization across multiple technical disciplines.
  • Significant ownership over architecture, engineering standards, delivery planning, and team development.
  • Direct involvement with infrastructure partners and hardware providers.
  • Opportunity to support advanced AI research, model training, and managed inference workloads.
  • International and distributed working environment with colleagues and partners across Europe and India.
  • Occasional opportunities for travel to partner locations and team events.
  • Opportunity to work at the intersection of high-performance computing, AI infrastructure, distributed systems, and cloud-native technologies.

How Jobgether Works
We use an
AI-powered matching process
to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice:
By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Это сохранённая копия объявления, опубликованного в другом месте. Вакансии снимают без предупреждения — перед откликом проверьте сайт работодателя. mentors.coach не является нанимающей стороной.

Скоро на этой странице

Резюме под эту вакансию — и билет в розыгрыш

Мы разбираем объявление до настоящих требований и переписываем ваше резюме под него — вопросами, а не выдумкой: ни одна строка не появится без вашего подтверждения. Войдите, чтобы получить это первым, — и попасть в розыгрыш.

  • Резюме под конкретную вакансию, а не «универсальное»
  • Ответы хранятся: правится любой, а не весь разговор заново
  • Всё в аккаунте — открывается с любого устройства

Разыгрываем

Скидка на сопровождение

Победителей выбираем случайно среди заявок с подтверждённой почтой. Дата розыгрыша и полные правила — на странице розыгрыша.

Правила розыгрыша

Backend Engineer

Senior Machine Learning Engineer

Randstad Hungary

Удалённоsenior

Откликнуться на сайте работодателя

Описание вакансии

Organisation/Department

Our client is a US-headquartered, market-leading enterprise in their sector with a multi-decade history and an agile, global network. We are seeking a highly skilled Senior
Machine Learning Engineer
to join their expanding Budapest team as a senior technical individual contributor. Situated within the Data Engineering organization, you will operate at the intersection of data engineering, applied ML, and software engineering to design, build, and deploy production-grade ML infrastructure and agentic AI systems that directly impact the business.

Job description

  • End-to-End ML Pipeline Engineering:
    Design, build, and maintain production ML pipelines end-to-end — feature engineering, model training, evaluation, deployment, serving, and monitoring on AWS and Databricks.
  • Agentic AI Architecture:
    Architect and implement agentic AI orchestration systems using frameworks like LangChain, LangGraph, CrewAI, or custom layers, with production-grade reliability, observability, guardrails, planning loops, and memory management.
  • Feature Stores & Data Pipelines:
    Build and optimize feature stores, training data pipelines, and feature engineering workflows serving both batch and real-time inference workloads.
  • MLOps Infrastructure & Governance:
    Own MLOps infrastructure including CI/CD for models, automated retraining pipelines, A/B testing frameworks, model versioning, experiment tracking, and ML asset governance using MLflow, Unity Catalog, and Databricks Model Serving.
  • LLM Integration Patterns:
    Design and implement LLM integration patterns including RAG architectures, prompt management systems, tool-use frameworks, vector databases, and memory/state management.
  • Monitoring, Observability & Evaluation:
    Develop model monitoring for drift detection, performance degradation alerts, cost tracking, and automated remediation. Establish evaluation frameworks for predictive models (standard ML metrics, backtesting) and agentic systems (task completion, hallucination detection, tool-use accuracy, latency budgets).
  • Technical Leadership & Collaboration:
    Drive build-vs-buy and framework selection decisions backed by prototypes and benchmarks. Mentor ML engineers through technical design reviews, code reviews, and architectural guidance.

Required Experience

  • Core Background:
    6+ years in machine learning engineering, applied ML, or closely related software engineering roles with recent, demonstrated production delivery.
  • Production ML at Scale:
    2+ years building and operating production ML systems handling real traffic and business-critical decisions (not just notebooks or proof-of-concepts).
  • Databricks ML & AWS Ecosystem:
    Production experience with Databricks ML ecosystem (MLflow, Model Serving, Feature Store, Unity Catalog) and supporting AWS services (SageMaker, Bedrock, S3, Lambda, Step Functions, ECS/EKS).
  • Agentic AI Production Systems:
    Hands-on experience building agentic AI systems (multi-step orchestration, tool use, planning loops, memory management, human-in-the-loop patterns).
  • Core Tech Stack & Software Engineering:
    Deep proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost) with strong software engineering fundamentals (testing, version control, code review, CI/CD).
  • LLM & Inference Experience:
    Production experience with LLM applications (RAG pipelines, vector databases like Pinecone/Weaviate/Chroma/pgvector, embeddings, prompt engineering, fine-tuning) and real-time/batch inference optimization (quantization, distillation, caching).

Preferred Qualifications

  • Experience with multi-agent system architectures (specialization, inter-agent communication, shared state management, failure recovery).
  • Production experience with model fine-tuning and RLHF/DPO alignment techniques.
  • Hands-on GPU infrastructure management, distributed training, and compute optimization on AWS (EC2 GPU, SageMaker training jobs, Bedrock custom models).
  • Familiarity with streaming ML (online learning, real-time feature computation, event-driven inference) and AI guardrail/safety systems (content filtering, output validation, cost controls).
  • Contributions to open-source ML tooling or published applied ML work.
  • MS or PhD in Computer Science, Machine Learning, or a quantitative field (practical production experience weighted equally).

Benefits

  • High Technical Impact:
    A unique professional challenge to shape production predictive AI models and agentic orchestration workflows for a stable, market-leading global enterprise.
  • Competitive Compensation:
    Senior level base salary and annual target bonus.
  • Benefits Package:
    Cafeteria allowance and private health insurance package.
  • Flexibility:
    Hybrid working model requiring 3 days of office presence (Budapest) and offering 2 days of Home Office per week.

Это сохранённая копия объявления, опубликованного в другом месте. Вакансии снимают без предупреждения — перед откликом проверьте сайт работодателя. mentors.coach не является нанимающей стороной.

Backend Engineer

Architecte Solutions logiciel Aéronautique/Défense

Capgemini Engineering

Удалённоlead

Откликнуться на сайте работодателя

Описание вакансии

Capgemini Engineering, leader mondial des services d'ingénierie , rassemble des équipes d'ingénieurs , de scientifiques et d'architectes pour aider les entreprises les plus innovantes dans le monde à libérer leur potentiel . Des voitures autonomes aux robots qui sauvent des vies, nos experts en technologies digitales et logicielles sortent des sentiers battus en fournissant des services uniques de R&D et d'ingénierie dans tous les secteurs d'activité . Rejoignez nous pour une carrière pleine d'opportunités , où vous pouvez faire la différence et où aucun jour ne se ressemble

Description du poste

Rejoignez Notre Centre D’Excellence Software Et Contribuez Au Développement De Solutions Innovantes Dans Les Secteurs De L’Aéronautique, Du Spatial, De La Défense Et Du Naval. Vous Interviendrez Sur Des Projets Stratégiques à Forte Dimension Technologique Autour Des Applications Web, Mobiles Et Cloud, Au Cœur Des Enjeux De Transformation De Nos Clients. Dans Ce Cadre, Vos Missions Seront De

  • Comprendre les besoins fonctionnels et applicatifs des clients et contribuer aux démarches d’avant-vente.
  • Concevoir des architectures logicielles robustes, évolutives et sécurisées pour des environnements critiques.
  • Développer et promouvoir des offres innovantes autour des technologies applicatives et cloud.
  • Piloter la cohérence entre les besoins du marché, la stratégie des solutions et les capacités internes.
  • Développer un réseau de partenaires et assurer une veille continue sur les évolutions technologiques du marché.

Description du profil

  • Diplômé(e) d’une école d’ingénieurs ou Bac+5, vous justifiez d’au moins 15 ans d’expérience en architecture logicielle dans un contexte industriel complexe ou critique
  • Vous disposez d’une expertise dans les secteurs Aéronautique, Spatial, Défense ou Naval et connaissez les standards associés
  • Vous maîtrisez les architectures distribuées, les API, les microservices, le cloud hybride et les enjeux de cybersécurité logicielle
  • Vous évoluez avec aisance dans plusieurs environnements techniques tels que C/C++, Java, Python, C#/.NET ou Go et possédez un niveau d’anglais avancé
  • Vous êtes reconnu(e) pour votre leadership technique, votre capacité à fédérer les équipes et votre esprit d’analyse.

3 raisons de nous rejoindre

Qualité de vie au travail
: accord de télétravail en France et à l’international, accord sur l’égalité professionnelle, la parentalité, l’équilibre des temps et la mobilité durable.

Apprentissage en continu
: certifications et formations en libre accès, accompagnement sur mesure avec votre career manager, parcours d’intégration sur 9 mois.

Avantages groupe & CSE
: plan actionnariat, activités à tarifs préférentiels, remboursement partiel vacances, remboursement de votre abonnement sportif ou culturel.

Nos engagements et priorités

Le groupe Capgemini encourage une culture inclusive dans un cadre multiculturel et handi-accueillant. En nous rejoignant, vous intégrez un collectif qui valorise la diversité, développe le potentiel de ses talents, s’engage dans des initiatives solidaires avec ses partenaires, et se mobilise pour réduire son impact environnemental sur tous ses sites et auprès de ses clients.

Leader mondial des services d’ingénierie et de R&D, Capgemini Engineering met en oeuvre une connaissance sectorielle approfondie avec la maîtrise des dernières technologies digitales et logicielles pour accompagner la convergence des mondes physique et numérique. Avec plus de 55 000 ingénieurs et scientifiques dans plus de 30 pays, nous aidons nos clients à accélérer leur transformation vers l'Intelligent Industry.

Get The Future You Want* |www.capgemini.com/fr fr

  • Capgemini, le futur que vous voulez

Это сохранённая копия объявления, опубликованного в другом месте. Вакансии снимают без предупреждения — перед откликом проверьте сайт работодателя. mentors.coach не является нанимающей стороной.

Backend Engineer

Asset Management & Systems Analyst

Accenture Argentina

Удалённо

Откликнуться на сайте работодателя

Описание вакансии

We are looking for an Asset Management & Systems Analyst to join our Supply Chain & Engineering team. In this role, you will collaborate on a project for a leading transportation company based in Canada, focused on improving control systems and inventory management.

As an Asset Management & Systems Analyst, you will support and optimize asset management systems and processes to improve asset performance, reliability, and lifecycle management. You will work closely with cross-functional teams, leveraging Enterprise Asset Management (EAM) platforms and digital tools to drive operational efficiency and data-driven decision-making.

👨‍💻 Key Responsibilities:

  • Support and optimize asset management systems and processes.

  • Collaborate with Operations, Maintenance, and Reliability teams to identify opportunities for improving asset performance.

  • Leverage data analytics and digital tools to enhance asset management practices.

  • Support the implementation of solutions for predictive maintenance and asset monitoring.

  • Contribute to the optimization of maintenance strategies.

  • Participate actively in team discussions and help resolve work-related challenges.

🎯
Must-have Skills:

  • Experience with Enterprise Asset Management (EAM) platforms such as SAP EAM, IBM Maximo, Hexagon EAM, or similar solutions.

  • Advanced English (the client is based in Canada, and the role requires regular interaction with international stakeholders).

  • Advanced SQL skills, including writing complex queries for asset and operational data analysis.

🚀 Nice-to-have Skills:

  • Experience with Hexagon EAM.

  • Knowledge of Asset Performance Management (APM) platforms.

  • Knowledge of Systems Engineering concepts.

  • Experience with predictive maintenance and asset monitoring.

  • Experience working with SCADA (Supervisory Control and Data Acquisition) systems.

  • Intermediate knowledge of Python.

  • Experience in transportation, manufacturing, utilities, or other asset-intensive industries.

🤳
Benefits We Offer You:

  • 🍔 Pedidos Ya delivery credits

  • 🏥 Swiss Medical premium healthcare plan at no cost for you and your immediate family

  • 🌐 Connectivity reimbursement

  • 🏋️ 100% covered gym membership

  • 🌴 Flexible vacation policy

  • ⏰ Flexible working hours

  • 📜 Sponsored certifications

  • 🎉 Day off on your birthday

  • 💰 Performance bonuses

  • 🗓 Accenture Days

  • 🎯 Flexible benefits package

  • 👶 Extended maternity & paternity leave

  • 🧸 Financial support for childcare

  • ➕ And many more!

  • We want you to have the tools you need to keep learning, growing, and making a difference in the world.

🌍
Location:
We have offices in
Buenos Aires, Córdoba, Mar del Plata, Rosario, Salta, and Mendoza
.

If you are based in other provinces, many of our positions are remote, so you can work from home.

🌈
Equality and Inclusion
At Accenture, equality drives innovation. We believe in building an inclusive and diverse workplace where everyone has equal opportunities.

All decisions related to recruitment and selection are made without distinction, exclusion, or preference based on race, color, gender, sexual orientation, disability, age, religion, political or union opinion, nationality, socioeconomic background, or any other characteristic protected by applicable law.

Это сохранённая копия объявления, опубликованного в другом месте. Вакансии снимают без предупреждения — перед откликом проверьте сайт работодателя. mentors.coach не является нанимающей стороной.

Backend Engineer

Développeuse / Développeur CRM - Stage

Capgemini

Удалённоparttimelead

Откликнуться на сайте работодателя

Описание вакансии

Choisir Capgemini, c'est choisir une entreprise où vous serez en mesure de façonner votre carrière selon vos aspirations. Avec le soutien et l'inspiration d'une communauté d’experts dans le monde entier , vous pourrez réécrire votre futur . Rejoignez nous pour redéfinir les limites de ce qui est possible, contribuer à libérer la valeur de la technologie pour les plus grandes organisations et participer à la construction d’un monde plus durable et inclusif

Vos missions

Vous rejoindrez une équipe intervenant sur des projets variés grâce à la diversité des secteurs d'activité (Banque, Media, Energie, Retail…).

Vous participerez aux missions suivantes :

Paramétrer et développer des applications digitales (CRM / e commerce)

Participer à l'intégration technique de solutions CRM et e-commerce sur mesure dans un contexte Agile.

Concevoir des applications sur les plans technique et fonctionnel.

Paramétrer des solutions Salesforce (SFDC), réaliser les tests et les recettes fonctionnelles, puis participer à leur déploiement.

Cette description n’est pas limitative. Elle peut tout à fait évoluer en fonction de votre expérience, des projets en cours et de vos attentes.

Votre profil

En M1/M2 dans le domaine du développement logiciel

Compétences en développement (Java, APEX).

Curiosité technologique et volonté d’apprendre

Aisance en anglais (niveau B2 minimum)

3 Raisons de nous rejoindre

Avantages groupe :
bénéficiez d’un ensemble d’avantages tels que les primes de cooptation, tickets restaurant, ainsi que des activités sociales et culturelles variées proposées par le CSE. Des dispositifs d’accompagnement à la parentalité, comme le temps partiel à 90% pendant les vacances scolaires, sont également disponibles, ainsi que de nombreux autres avantages issus de nos accords collectifs.

Qualité de vie au travail :
profitez d’un équilibre entre vie professionnelle et personnelle, d’une possibilité de télétravailler (en France et à l’international), ainsi que des dispositifs de santé et bien-être (ligne d'écoute, plateforme dédiée...).

Environnement inclusif :
rejoignez des réseaux engagés comme Women@Capgemini, Parents@Capgemini, OUTfront ou CapAbility, et évoluez dans un cadre certifié EDGE+ et reconnu par le Bloomberg Gender Equality Index.

Happy Trainees :
notre engagement envers les jeunes talents est reconnu dans le classement HappyTrainees, preuve que chez nous, les stagiaires et alternants ne viennent pas juste apprendre… ils viennent s’épanouir !

Notre engagement et priorités

Le groupe Capgemini encourage une culture inclusive dans un cadre multiculturel et handi-accueillant. En nous rejoignant, vous intégrez un collectif qui valorise la diversité, développe le potentiel de ses talents, s’engage dans des initiatives solidaires avec ses partenaires, et se mobilise pour réduire son impact environnemental sur tous ses sites et auprès de ses clients.

A propos de Capgemini

Capgemini est un leader mondial, responsable et multiculturel, regroupant près de 350 000 personnes dans plus de 50 pays. Fort de 55 ans d’expérience, nous sommes un partenaire stratégique des entreprises pour la transformation de leurs activités en tirant profit de toute la puissance de la technologie et des innovations dans les domaines en perpétuelle évolution tels que le cloud, la data, l’Intelligence Artificielle, la connectivité, les logiciels, l’ingénierie digitale ou les plateformes.

Capgemini, partenaire de la transformation business et technologique de ses clients, les accompagne dans leur transition vers un monde plus digital et durable, tout en créant un impact positif pour la société. Le Groupe, responsable et multiculturel, rassemble 340 000 collaborateurs dans plus de 50 pays. Depuis plus de 55 ans, ses clients lui font confiance pour répondre à l'ensemble de leurs besoins grâce à la technologie. Capgemini propose des services et solutions de bout en bout, allant de la stratégie et du design jusqu'à l'ingénierie, en tirant parti de ses compétences de pointe en intelligence artificielle et IA générative, en cloud, et en data, ainsi que de son expertise sectorielle et de son écosystème de partenaires.

Это сохранённая копия объявления, опубликованного в другом месте. Вакансии снимают без предупреждения — перед откликом проверьте сайт работодателя. mentors.coach не является нанимающей стороной.

Ещё 1 007 вакансий по этой категории в этой стране

Technical Lead - GPU InfrastructureJobgether

Откликнуться на сайте работодателя