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AI Engineer (Machine Learning & Generative AI)
Build and deploy production ML and GenAI components—models, RAG systems, agents, and pipelines—using Python, SQL, and cloud services to power Amgen’s healthcare-focused AI products.
Machine Learning Engineer
Build, deploy, and monitor ML models and MLOps pipelines on AWS for forecasting and GenAI apps in a biotech setting.
Data Engineer - Tech Lead (Databricks, Pyspark)
Lead the design and build of scalable cloud-native data platforms using Azure Databricks, PySpark and Lakehouse principles, optimizing ETL workflows and streaming pipelines for enterprise-grade analytics.
Data Scientist IA F/H
Build, train, and deploy AI models (ML, DL, generative, RAG, agents, computer vision) in Python, then wrap them in APIs for production use.
Sr. Vehicle Modeling Engineer, Applied AI Systems
Build and operate AI-driven Digital Twin systems for electric vehicles, using Python, OpenModelica, and LLM tooling to simulate, test, and validate vehicle controls and infotainment before hardware is available.
Staff Software Development Engineer, AI Platform
Build and scale secure AWS infrastructure (EKS, Lambda, Terraform) for AI/ML workloads, automate CI/CD with GitLab, and run a centralized observability stack (Prometheus/Grafana) to support production LLM inference and vector databases.
AI/ML Engineering Manager
Lead a team of ML engineers and architects at an AI-first cloud services company, owning hiring, team growth, and complex customer engagements while shaping AI/ML architectures and driving pre-sales.
AI Engineer
Build and maintain AI agent toolkits that let models take real actions in enterprise systems, ensuring reliability, security, and governance for Fortune 100 deployments.
Vice President, Data Science & Generative AI
Lead generative AI and fraud-detection models at a global bank, building LLM apps, prompt engineering, and RAG pipelines to cut fraud losses and false positives.
LLM / Agentic AI / Full-Stack AI Engineering
Senior full-stack AI engineer building LLM-based agents and retrieval systems using RAG, embeddings, and vector databases with PyTorch and AWS Bedrock.
AI Engineer Middle / Middle+ [AI Team]
Designs and builds AI systems using LLMs, RAG, and OCR to automate workflows and enhance productivity, working with Python, Go, and cloud/AWS tools.
Automation Stream Lead [Customer IT Support]
We are looking for an Automation Stream Lead to join our Automation team. The Automation team is responsible for building and scaling internal automation solutions that optimize business processes across Plata. We…
Senior Data Engineer (AI/LLM)
Builds cloud-native data pipelines and RAG architectures for LLM systems using Databricks, Spark, and vector search on Azure/GCP.
Ведущий инженер по моделям машинного обучения (RAG+LLM)
Senior ML engineer builds production-grade RAG pipelines and multi-agent systems to automate corporate knowledge tasks using LLMs, vector DBs, and FastAPI services.
Member of Technical Staff - Applied AI Engineering [Bay Area]
Build and deploy enterprise-grade AI agents that integrate with regulated workflows, customize models for customer domains, and own production systems from prototype to scale.
AI Software Developer
Build and deploy AI-powered transport applications using LLMs, computer vision, and agentic systems to optimize Singapore’s land transport network.
Дата аналитик в команду разработки AI Бизнес-помощника (СберБизнес)
Data Analyst building data pipelines and semantic models for an AI Business Assistant in SberBank’s SME banking unit, optimizing SQL queries and ETL flows to power GenAI-driven recommendations.
AI Developer with Python for Customer Care AI Platform team (hybrid)
At IONOS, the leading European provider of cloud infrastructure, cloud services and hosting services, you will work together with a wide range of teams. We are characterized by open structures, a friendly working…
Site Reliability Engineer, AI Enablement (Remote)
Advise and enable engineering teams on AI adoption, focusing on LLM integration, RAG pipelines, and agentic architectures while ensuring reliability, observability, and governance compliance in healthcare AI systems.