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ML Engineer (ML/LLM Ops)
Build and operate ML/LLM platforms for a Korean neobank, focusing on stable, scalable, and secure model training, deployment, and serving using tools like MLflow, Kubeflow, Triton, and vLLM.
AI Engineer
An AI Engineer who designs, develops, and deploys machine learning models for production — building training/evaluation pipelines, monitoring model performance, and integrating AI into applications alongside data scientists and product teams. Core stack is Python with TensorFlow/PyTorch/scikit-learn, cloud platforms, and ML Ops tooling.
Lead Engineer/ Engineer, DevOps & MLOps (AI Platform), xCloud
Engineer on HTX's xCloud team building the AI platform for Singapore's public safety agency: designing ML infrastructure (Kubeflow, MLflow, RunAI), automating CI/CD and ML pipelines with DevSecOps practices, and writing infrastructure-as-code on-site in Singapore.
Senior Data Platform Engineer - Data Platform Team
Senior engineer on Surf AI's Data Platform Team designing, building, and scaling the data infrastructure that processes enterprise security event data — batch and real-time pipelines, data modeling, ML/LLM workflows, and production reliability. Core stack: Python, SQL, Spark, cloud infra (AWS, Kubernetes, IaC).
Staff Backend Engineer: Distributed Data & AI Platform
Staff backend engineer at Databricks' new Vancouver R&D hub, building large-scale distributed features for its data and AI platform across teams like Log Analytics, AI/BI, Unity Catalog, and Databricks Apps. Core work spans backend systems in Java/Scala/C++, distributed systems, SQL, and cloud infrastructure (AWS/Azure/GCP, Docker, Kubernetes).
Senior Fullstack Engineer — Data & AI Platform
Senior fullstack engineer building customer-facing features for Databricks' data and AI platform teams in Vancouver (Log Analytics, AI/BI, Unity Catalog, Databricks Apps). Day to day spans front-end UX with modern JavaScript frameworks and large-scale distributed backend services using SQL, cloud, and Kubernetes.
Generative AI Engineer
Dellent is a consulting company focused in System Information and Telecommunications. Our goal is to help our candidates and consultants to take a step forward in their careers through projects that meet their needs…
Senior Data Scientist (Ml Engineer) Ova5861
Senior ML Engineer (12-Month Contract) Location: Hybrid We are seeking a Senior Machine Learning Engineer for a 12-month contract to operationalize, scale, and manage production-grade ML, AI, and GenAI solutions. You…
Data Platform & AI Engineer
Owns Camelina Company España's Databricks environment end to end: building ETL/ELT and streaming pipelines (PySpark, SQL, Delta Lake), deploying ML/AI solutions (forecasting, anomaly detection, LLM/RAG), and creating dashboards with Power BI/Tableau. Works with business teams in Spain and the US from a Madrid office/home-office base.
Senior Data Engineer
A senior AI/technology leadership role in Madrid: the person defines the tech roadmap, leads a multidisciplinary team of up to 10, and ships production AI/ML, generative-AI, and automation solutions for enterprise customers using Python, TensorFlow/MLflow, OpenAI/Anthropic-class LLMs, AWS/GCP, Docker/Kubernetes, and CI/CD pipelines.
Data Engineer Databricks
Designs and builds scalable Databricks data pipelines in Singapore — batch and real-time ingestion with PySpark, Delta Lake, and Unity Catalog governance, plus CI/CD (Terraform, Git) and MLflow support. Requires 5+ years of data engineering experience and Singapore PR status.
Analyst, Data Science & AI
What are your contributions to the team? Translate business challenges into measurable forecasting, optimization, NLP, retrieval, classification, risk, or recommendation problems. Explore, profile, and validate…
Senior Lead Applied AI Scientist
Lumen is the trusted network for the AI‑powered world, connecting people, data, and applications through our expansive fiber network and connected ecosystem. We enable secure, high‑performance connectivity across…
Consultor MLOps
Capgemini is hiring a Senior MLOps Consultant in Madrid to design, automate, and optimize machine learning pipelines using Databricks, MLflow, Delta Lake, and Spark on Azure/AWS, covering CI/CD, model governance, monitoring, and infrastructure, while mentoring within the Data & AI team.