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Lead the design and implementation of enterprise-grade Generative AI and Agentic AI solutions—spanning RAG, LLMs, and AI agents—using frameworks like LangChain, LangGraph, vector databases, and cloud-native infrastructure on a 12-month contract.
Build and deploy scalable ML and GenAI solutions at Amgen, turning prototypes into production-ready services using Python, cloud platforms, MLOps and containerization.
Hands-on delivery leadership role embedding AI, generative AI and LLM methods into supply chain analytics workflows at Applied Materials, using SQL, Python, Databricks and enterprise MLOps platforms to turn manual analyses into governed, automated tools.
Build and maintain the data infrastructure and automation for an AI team’s ML platform, focusing on Linux servers, VMs, offline-capable environments, and tools like MLflow/DVC/ClearML.
Lead a team of data engineers to build and optimize AutoZone's GCP Data Lakehouse platform, designing end-to-end data pipelines and ensuring governance, performance tuning, and scalability using GCP, Apache Spark, Delta Lake, and PySpark.
Principal ML Engineer owning the end-to-end architecture of Disney's News & Entertainment ML platform, driving personalization and recommendation systems at scale across ABC News, National Geographic, Marvel, and Disney Studios using AWS, Spark, Kafka, and big data technologies.
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.
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.
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.
Immer eine passende Lösung und das Fundament zum Erfolg Wir sind der Verband der Vereine Creditreform, der High-Tech-Service-Dienstleister für unsere 128 Standorte in Deutschland. Über 140 Jahre Wissen & Erfahrung…
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.
New Permanent Opportunity for a DV Cleared Senior Data Scientist in Cheltenham for a leading National Security and Defence Consultancy client. Must have active DV Clearance Up to £85k DoE plus bonuses and benefits 3…
Job Advertisement: Senior Data Scientist Location: Welwyn Garden City Contract Type: Fixed Term Contract Contract Length: 12 months (6+6) Daily Rate: £550 - £800 per day Inside IR35 Working Pattern: Hybrid About the…
Vill du utveckla AI-lösningar som skapar verklig nytta – tillsammans med människor från olika delar av verksamheten? Vi söker en utåtriktad och samarbetsorienterad AI Engineer till vårt Data-team. Om tjänsten Som AI…
Builds and deploys ML models for Firecrawl’s search and data extraction systems, focusing on ranking/relevance, LLM-driven features, and A/B testing frameworks.
You engineer production-grade ML systems for rail-inspection data, turning prototypes into reliable, scheduled pipelines and APIs that run on AWS and handle years of sensor data.
The ML Developer will build and scale machine learning models and data pipelines for Sber's behavioral science laboratory. The role involves fine-tuning LLMs, designing RAG architectures, and deploying production-ready AI solutions using a stack including Python, FastAPI, and various MLOps tools.
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