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Leads the design and evolution of Target’s enterprise AI/ML platform, defining architecture for scalable, cloud-native ML lifecycle management, deployment, governance, and observability to enable cross-functional teams to build and deploy AI solutions at scale.
Staff ML Engineer specializing in generative AI for voice and speech, designing scalable AI-powered features and infrastructure to enable product innovation at Weave. Focuses on audio/voice models, LLMs, RAG, and distributed systems for large-scale B2B applications.
Build and lead ML infrastructure for voice/GenAI at scale, enabling teams to ship AI-powered features while democratizing ML tooling for developers.
Lead AI-driven transformation for global manufacturing and supply operations, deploying agentic systems and LLMs to optimize processes and KPIs across Opella’s network.
Build and deploy ML models and data pipelines in Python/SQL, optimizing for production performance and real-time insights in a cloud environment.
Maintain and optimize core ML systems for a large FTSE 100 company, debugging data flows and forecasting models using Python, GCP, and Vertex AI.
Build and deploy ML models to optimize healthcare copay programs and extract insights from pharmaceutical data using Python, R, and MLOps tools.
Design and implement scalable MLOps/LLMOps pipelines on AWS, including SageMaker, EKS, and CI/CD, to deploy and monitor production-grade AI models for enterprise clients.
Design and deploy enterprise AI solutions on Red Hat OpenShift AI, including GenAI, agentic AI, and MLOps workflows, while advising customers and leading project teams.
Build and deploy scalable ML infrastructure and real-time recommendation systems in Python/Go, collaborating with data scientists to drive user engagement for Shipt’s personalization platform.
Design and maintain AWS cloud infrastructure for AI/ML systems, including GPU clusters, CI/CD pipelines, and observability, while collaborating with AI engineers and data scientists.
Senior Software Engineer building and operating workflow orchestration platforms (Argo Workflows, Airflow) to power autonomous truck development, ML training, and CI/CD pipelines on Kubernetes and AWS.
Field engineer helping global partners (OEMs, cloud providers, integrators) adopt Ubuntu, Kubernetes, OpenStack and open-source stacks; designs joint solutions and runs technical workshops worldwide.
This is an opportunity to run a field engineering team, helping customers understand and implement Canonical's open source solutions in public clouds and in their own data centers. We work across the entire…
This is an opportunity to run a Professional Services team (also known as Field Engineering) team, helping customers understand and implement Canonical's open source solutions in public clouds and in their own data…
Design and validate cloud-native solutions (Kubernetes, OpenStack, AI/MLOps) for Canonical’s global partners, integrating Ubuntu and open-source stacks across public/private clouds.
Lead a global team of engineers to build and maintain MLOps and analytics infrastructure using Kubeflow, MLFlow, and Feast, while mentoring engineers and driving team productivity.
Drive product strategy for open-source software at Canonical, collaborating with global teams to deliver Ubuntu and related solutions across AI, cloud, IoT, and enterprise markets.
Design and deploy AI/ML infrastructures and MLOps solutions on Ubuntu, Kubernetes, and cloud platforms for global enterprises, using open-source tools like Kubeflow and MLFlow.
Drive open-source product strategy at Canonical, shaping Ubuntu and adjacent offerings across AI, cloud, IoT, and enterprise verticals while collaborating with global teams.
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