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At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can…
Lead MLOps management at Singtel Group, ensuring ML model stability, performance, governance, and incident handling using MLFlow and Databricks.
Design, build, and optimize enterprise AI solutions using LLMs (OpenAI, Azure OpenAI, Google Gemini), RAG architectures, vector databases, and Python-based cloud-native development.
Design and operate CI/CD pipelines for AI/ML deployments in a regulated banking environment, using Docker, Kubernetes/OpenShift, Terraform, Ansible, Prometheus, and Grafana while deploying LLMs from Hugging Face.
AI DevOps/MLOps Engineer building and automating CI/CD pipelines for LLM and AI model deployment on Kubernetes/OpenShift, using Jenkins, Docker, Terraform, and model serving platforms for a Singapore-based bank.
DevOps Engineer for AI systems: designs and maintains CI/CD pipelines, observability, and cost/performance management for LLM/agentic applications, bridging POCs to production-grade deployments with Kubernetes and Terraform.
Мы разрабатываем инновационную платформу на основе генеративного искусственного интеллекта (GenAI), предназначенную для автоматизации создания и управления маркетинговыми кампаний. Основной целью нашего продукта…
Builds and deploys GenAI, Agentic AI, and NLP models to enhance customer service in SMSF/wealth banking, focusing on productionizing AI solutions, governance, and responsible AI practices.
Data Engineer building and maintaining scalable data pipelines, warehouses, and data services on GCP (BigQuery, Airflow, Dataform/DBT, Pub/Sub, Cloud Functions) for a multi-carrier shipping SaaS platform, with an AI-augmented insights focus.
The Principal AI Software Developer leads the design and implementation of large-scale, mission-critical AI and LLM systems for federal agencies using a modern cloud stack including Next.js, Terraform, and major cloud providers. This hands-on role involves architecting AI solutions, establishing MLOps practices, and ensuring compliance with federal security and AI policy standards.
Design and architect enterprise data platforms, pipelines, data models, and visualizations for federal government clients, spanning data engineering, BI, and data science. Core technologies include AWS services, Databricks, Spark, Kafka, SQL databases, and Python.
A Senior Data Engineer (ML) transforms data science prototypes into production-ready, scalable AI solutions by leading MLOps, CI/CD, and model monitoring. They collaborate with data scientists to optimize ML pipelines, ensure data quality, and champion responsible AI practices for government use.
Senior Data & AI / MLOps Engineer responsible for industrializing and deploying ML models, LLMs/AI agents, and data pipelines into production within the financial sector, using Python, PySpark, AWS, Docker, Kubernetes, and MLflow.
Data & AI Engineer at Allianz Services designing, building, and productionizing ML models and data pipelines using Python, classical ML frameworks (LightGBM, XGBoost, Scikit-Learn), Docker, Kubernetes, and Azure, in a hybrid role based in Barcelona.
Data Engineer focused on Data Products, operationalizing AI/ML models into reliable, scalable data products (batch and real-time pipelines) using Python, SQL, Spark, Databricks, Airflow, and GCP/Azure within a leading European retail company's Digital Hub in Barcelona.
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we’re tapping into the unlimited potential of AI to define the next era of computing–an era in which…
Responsibilities Conduct comprehensive cloud security assessments, evaluating designs, configurations, and implementations across major cloud service providers (CSPs) including AWS, Azure, and GCP. Architect and drive…
Lead AI/ML strategy and analytics for JPMorgan Chase’s Card business, translating business needs into data-driven solutions and mentoring a high-performing analytics team.
The Senior DevOps Engineer will design, automate, and manage scalable Azure cloud infrastructure and CI/CD pipelines for enterprise applications. The role focuses on DevSecOps, container orchestration, and supporting AI/ML infrastructure using tools like Terraform, Kubernetes, and Azure DevOps.
The Engineering Manager will lead a team of Machine Learning Engineers to design and deploy production-ready LLM applications and agentic AI systems for healthcare clinical workflows. The role focuses on building scalable AI infrastructure, MLOps workflows, and collaborating across teams to translate research into clinical products.
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