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Design and develop AI-powered applications, agentic workflows, and intelligent search systems using LLMs, RAG, and cloud-native platforms as part of Altera's Quartus AI team.
Build, deploy, and continuously improve production AI features (search, personalization, content generation, copilots) on Microsoft Foundry/Azure AI, grounded in Microsoft Fabric/One Lake data, while establishing MLOps practices and mentoring junior engineers.
Principal ML Engineer owning the end-to-end architecture of Disney's News & Entertainment ML platform, driving personalization and recommendation systems at scale across brands like ABC News, Marvel, and Disney Studios using AWS, Spark, Kafka, and deep learning.
The Director of Data Science will lead a team in developing and deploying AI/ML models to improve patient care and operational efficiency at CenterWell. This role involves collaborating with product, engineering, and clinical teams to manage the full AI lifecycle, from prototyping to production, while ensuring adherence to responsible AI standards.
Designs and oversees large-scale data and AI architectures, balancing latency, cost, and scalability for Michelin’s enterprise systems. Focuses on Lakehouse (Delta Lake/ADLS Gen2), ML pipelines (Azure ML/AKS), and data models (PostgreSQL/Snowflake) while ensuring security and compliance.
This role involves developing embedded software and video analytics solutions using modern C++ and Python. The engineer will work on edge AI workloads, MLOps pipelines, and distributed system architectures.
Develops embedded and AI-driven video analytics solutions, integrating C++/Python for Linux-based systems, distributed messaging, and MLOps pipelines while optimizing for edge hardware.
Azure AI Data Architect designing and implementing enterprise-scale data platforms and AI/GenAI solutions on Microsoft Azure, partnering with stakeholders across client engagements at a global consultancy.
The Technical Architect will design and implement scalable, fault-tolerant AI systems on Google Cloud, bridging the gap between research and production. The role involves leading MLOps lifecycles, defining compute strategies for AI workloads, and mentoring teams to build resilient, cloud-native architectures.
Senior Data Scientist leading AI/ML and physics-based model development for a DTRA/DIA national security contract, using Python/R in classified JWICS environments to characterize hardened facilities and WMD processes.
Principal Data Scientist Farm Bureau Financial Services is seeking an experienced Principal Data Scientist to provide technical leadership across the full analytics lifecycle, from problem definition and model…
Our client is building the leading platform for computer vision and physical AI. More than one million developers use the platform to manage image data, annotate datasets, train models, and deploy computer vision…
Designs and optimizes large-scale data platforms and AI/ML architectures using Databricks, Spark, Delta Lake, and Unity Catalog, ensuring scalability, security, and performance across cloud environments.
Build and deploy AI/ML models and GenAI features for federal applications, integrating them into production systems and collaborating with cross-functional teams.
Machine Learning Engineer Location: Flexible (Hybrid) Working set up: Hybrid Salary: Competitive + bonus + benefits SPG are working on behalf of an established financial services organisation investing heavily in its…
Job Title: Independent End Point Assessor - Data & AI Job ID: 11922 Location: UK Remote / Home Based (fully remote) Job Type: Permanent Salary: Up to £60k Industry: Education Assessing across: Data Engineer Level…
AI Engineer designing and deploying AI/ML solutions on Azure (Azure ML, Cognitive Services, Synapse) to optimize tax, audit, and advisory workflows at a large CPA and advisory firm.
Leads AI/ML product strategy for data-quality and evaluation systems, defining roadmaps for agentic workflows, synthetic data, and expert contributor tools to improve AI-ready dataset delivery.
Own the roadmap for internal infrastructure, data, and security platforms at an AI company, coordinating engineering pods and translating business needs into prioritized technical projects.
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