Senior Machine Learning Ops Engineer IRC267638
Opportunité de Carrière : Senior Machine Learning Ops Engineer chez GlobalLogic
Présentation de l’Entreprise
GlobalLogic est un acteur majeur dans le domaine des produits et technologies de données, engagé à transformer le marketing grâce à une plateforme de données rapide et connectée. Avec une présence dans 20 marchés à travers le monde et une équipe de plus de 1 000 personnes, l’entreprise se consacre à intégrer la technologie, les données et l’analytique pour offrir des solutions innovantes dans le secteur de la publicité digitale.
Détails du Poste
Titre du poste : Senior Machine Learning Ops Engineer (IRC267638)
Localisation : Ukraine
Date de publication : 03 Juillet 2025
À propos du Rôle
En tant que premier Machine Learning Operations (MLOps) Engineer au sein de l’équipe, le candidat jouera un rôle clé en facilitant la connexion entre l’ingénierie de plateforme, la science des données et l’ingénierie logicielle. Ce poste implique la création de systèmes pour le déploiement, le suivi et l’évolutivité des modèles de machine learning, souvent en relation avec des équipes pluridisciplinaires.
Responsabilités Principales
- Déploiement et Opérations des Modèles : Assurer le déploiement, la surveillance et la maintenance des modèles en environnement de production.
- Gestion des Infrastructures et Pipelines : Concevoir et mettre en œuvre des pipelines MLOps évolutifs pour l’ingestion et la transformation des données.
- Collaboration avec les Équipes : Travailler en étroite collaboration avec les scientifiques des données et les ingénieurs logiciels pour intégrer les systèmes de machine learning dans des plateformes plus larges.
- Expertise en Cloud et Big Data : Utiliser les services cloud pour un stockage et un traitement de données évolutifs.
Compétences Requises
Compétences Techniques :
- Excellente maîtrise de Python et connaissances d’autres langages comme Clojure sont un plus.
- Expertise sur les plateformes cloud (AWS, GCP) et les entrepôts de données comme Snowflake ou BigQuery.
- Connaissance approfondie des frameworks MLOps (ex : Kubeflow, MLflow).
- Expérience en containerisation (Docker) et orchestration (Kubernetes).
Connaissances en Machine Learning :
- Bonne compréhension des principes de machine learning, évaluation des modèles et workflows de retraining.
- Pratique des frameworks ML tels que TensorFlow ou PyTorch.
Compétences Interpersonnelles :
- Compétences en communication pour collaborer efficacement.
- Esprit de résolution de problèmes, capable de travailler dans des environnements agiles.
Culture d’Entreprise
GlobalLogic privilégie un environnement inclusif où l’épanouissement personnel est encouragé. L’entreprise se consacre également à la formation continue, permettant aux employés d’explorer de nouvelles compétences et d’avancer dans leur carrière. En outre, un équilibre entre vie professionnelle et personnelle est valorisé, permettant aux collaborateurs de s’épanouir tant sur le plan professionnel que personnel.
Avantages Proposés
- Culture de soins : Priorité au bien-être et à l’intégration des employés.
- Opportunités de croissance : Accès à des formations et des outils de développement personnel.
- Travail significatif : Participation à des projets ayant un impact direct sur le marché.
- Flexibilité : Diverses modalités de travail pour concilier vie professionnelle et personnelle.
Postuler
Si vous êtes intéressé par cette offre et que vous répondez aux critères, nous vous invitons à postuler dès maintenant.
Cette annonce constitutionne une opportunité significative dans un secteur dynamique et en plein essor. Les candidats sont encouragés à vérifier l’intégrité de l’offre et à se rapprocher des valeurs d’égalité et de diversité prônées par GlobalLogic.
📅 Date de publication de l’offre : Thu, 03 Jul 2025 02:22:38 GMT
🏢 Entreprise : GlobalLogic
📍 Lieu : Украина
💼 Intitulé du poste : Senior Machine Learning Ops Engineer IRC267638
💶 Rémunération proposée :
📝 Description du poste : DescriptionWho is our client:
Our client is a global data products and technology company. They are on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation.
They work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. Delivering this through the AI-enabled media and data platform for the next era of advertising.
The client is endlessly curious. Their team of thinkers, builders, creators and problem solvers are over 1,000 strong, across 20 markets around the world. Our client’s culture is based on mutual trust, sharing, building, and learning together. They value simplicity, maintainability, automation, and metrics.About this role:
Client’s team consists of 100+ engineers, designers, data scientists, implementation, and product people, working in small inter-disciplinary teams closely with creative agencies, media agencies, and with our customers, to develop and scale our leading digital advertising optimization suite that delivers amazing outcomes for brands and audiences.
Client’s platforms are built with Python, React, and Clojure, are deployed using CI/CD, heavily exploit automation, and run on AWS, GCP, k8s, Snowflake, BigQuery, and more. They serve 9 petabytes and 77 billion objects annually, optimize thousands of campaigns to maximise ROI, and deliver 20 billion ad impressions across the globe. You’ll play a leading role in significantly scaling this further.
As client’s first Machine Learning Operations (MLOps) Engineer on the team, you will play a pivotal role in bridging the gap between platform engineering, data science, and software engineering, building systems that drive the deployment, monitoring, and scalability of machine learning models. You will design and implement pipelines, automate workflows, and optimise model performance in training and production environments. You’ll lead the creation of process, implementation of tools, and creation of solutions mature how we integrate machine learning solutions into our production systems, while maintaining reliability, security, and efficiency. You’ll additionally play a leading role in driving continuous improvement in model lifecycle management, from development to deployment and monitoring.#LI-AR1RequirementsTechnical Skills:
- Proficiency in Python for ML development; familiarity with additional languages like Clojure is a plus.
- Expertise in cloud platforms (AWS, GCP) and data warehouses like Snowflake or BigQuery.
- Strong knowledge of MLOps frameworks (e.g., Kubeflow, MLflow) and DevOps tools (e.g., Jenkins, GitLab, Flux)
- Experience with containerization (Docker) and orchestration (Kubernetes)
- Experience with infrastructure-as-code tools like Terraform
Machine Learning Knowledge:
- Solid understanding of machine learning principles, including model evaluation, explainability, and retraining workflows.
- Hands-on experience with ML frameworks such as TensorFlow or PyTorch
Big Data Handling:
- Proficiency in SQL/NoSQL databases and distributed computing systems like Dataprov, EMR, Spark, Hadoop
Soft Skills:
- Strong communication skills to collaborate across multidisciplinary teams.
- Problem-solving mindset with the ability to work in agile environments
Experience:
- At least 4+ years in platform, software, or MLOps engineering roles
- Proven track record of deploying scalable ML solutions in production environments
Job responsibilitiesModel Deployment and Operations:
- Deploy, monitor, and maintain machine learning models in production environments.
- Automate model training, retraining, versioning, and governance processes.
- Monitor model performance, detect drift, and ensure scalability and reliability of ML workflows
Infrastructure and Pipeline Management:
- Design and implement scalable MLOps pipelines for data ingestion, transformation, and model deployment.
- Build infrastructure-as-code solutions using tools like Terraform to manage cloud environments (AWS, GCP)
Collaboration with Teams:
- Work closely with data scientists to operationalize machine learning models.
- Collaborate with software engineers to integrate ML systems into broader platforms
Cloud and Big Data Expertise:
- Utilize cloud services from AWS, GCP, and Snowflake for scalable data storage and processing.
DevOps Integration:
- Implement CI/CD pipelines and automations to streamline ML model deployment.
- Use containerization tools like Docker and orchestration platforms like Kubernetes for scalable deployments
- Use Observability platforms to monitor pipeline and operational health of model production, delivery and execution
What we offerCulture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders.Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.About GlobalLogicGlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.
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