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Senior Data AI Engineer / MLOps Engineer – Productivización de Soluciones de IA
Senior Data & AI Engineer / MLOps Engineer productivizing AI solutions, responsible for ML model lifecycle, data pipelines, and production deployment using Python, PySpark, SQL, AWS, Docker, Kubernetes, CI/CD, Git, and MLflow.
DevOps Engineer - CI/CD - Barcelona, Madrid o Zaragoza, Alicante - madrid
This DevOps Engineer role focuses on managing CI/CD pipelines, cloud infrastructure, and container orchestration for a Conversational AI platform. The position requires expertise in Azure DevOps, Terraform, Helm, and Kubernetes, while collaborating with development and AI teams.
AI Engineer (LLM)
Design, develop, and deliver enterprise AI solutions using LLMs, RAG, and AI agents on Microsoft Azure, integrating them into business workflows for global clients.
Product Designer, Defense
Product Designer owning end-to-end design of real-time operator interfaces and enterprise web platforms for autonomous defense systems at Applied Intuition, using modern prototyping tools.
Applied AI & Data Engineer - Business & Education
Build and deploy AI-native data infrastructure at Apple scale, designing LLM agents, retrieval systems, and evaluation pipelines to transform how users access iCloud content across devices.
Lead Data Analyst
Lead Data Analyst partnering with clients to design marketing analytics strategies, build predictive/segmentation models, and translate multi-channel data into business outcomes using Python, R, SQL, and ML techniques.
Machine Learning Engineer - AI
Fine-tune and optimize Small Language Models (SLMs) for edge, mobile, and local deployment using Hugging Face, LoRA, QLoRA, and PEFT, while building end-to-end MLOps pipelines spanning the full ML lifecycle.
AI/ML Engineer
An AI/ML Engineer at Nexstar Media Group designs, builds, and deploys machine learning and agentic AI systems for real-world products, working across the full ML lifecycle from data preparation to model monitoring and iteration.
MLOps Engineer (Junior)
Junior MLOps Engineer responsible for automating ML pipelines (CI/CD for ML), deploying models to production using Kubeflow and MLflow, and monitoring data drift and model performance. Core technologies include Python, Docker, Kubernetes, Kubeflow, and MLflow.
Senior Program Manager, Agentic Ai
Lead the design and deployment of multilingual AI systems at Uber, evaluating LLMs and building scalable pipelines to automate localization workflows while balancing quality, cost, and latency.
Manager I, Data Scientist
Kroll is hiring a Data Science Manager to lead and grow our data science function within the Enterprise Data Group. This role sits at the intersection of technical leadership and strategic delivery — you will shape how…
Senior Data Scientist
Senior Data Scientist designs and deploys ML models (traditional, deep learning, NLP, LLM/GenAI) on Azure/Databricks to solve fintech risk and compliance challenges.
Lead AI/ML Platform Engineer
Designs and builds scalable cloud-native AI/ML and GenAI infrastructure for Toyota Financial Services, focusing on MLOps/LLMOps, GPU-accelerated compute, and secure model deployment at enterprise scale.
Senior Principal AI & Machine Learning Engineer, Spring, Texas, Onsite
Lead the design, development, and deployment of AI/ML-powered applications and microservices on Kubernetes, using MLOps/AIOps tools and cloud platforms to deliver scalable, production-grade solutions.
Data Science Team Lead - Sr. Principal Engineer – Commercial DPHM P5 (Onsite)
Date Posted: 2026-08-19 Country: United States of America Location: US-CT-EAST HARTFORD-ETC ~ 400 Main St ~ BLDG ETC Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: This job…
Lead Systems Designer
Lead the technical design of enterprise systems for plasma-derived therapies, using modern web stacks and cloud-native patterns while embedding AI capabilities and mentoring engineers.
Senior Program Manager, Agentic Ai
Lead the design and rollout of multilingual GenAI localization pipelines using LLMs on GCP, balancing quality, cost, and latency while partnering with engineering and MLOps.