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Develops and integrates AI-driven solutions into software, collaborating with data and engineering teams to deploy scalable AI models and optimize intelligent systems for production.
Designs and builds an enterprise MLOps platform for AI/ML workflows, focusing on scalable services, APIs, and developer tooling to enable ML teams to deploy and manage models at scale.
Senior DevOps Engineer builds and secures cloud-native infrastructure, automates CI/CD pipelines, and sets engineering standards for a product company serving fintech, e-commerce, edtech and AI clients.
The Demo Infrastructure Engineer will manage and automate the demo environments for the Loops Agentic AI platform, ensuring high availability and scalability for field sales teams. The role involves using DevOps principles, cloud infrastructure, and scripting to create reliable, repeatable, and cost-optimized demo instances.
Builds and maintains the infrastructure for AI-native email triage systems, focusing on model training, deployment, inference, and observability to ensure scalable, low-latency AI workflows.
The Technical SME / Technical Business Analyst supports AI-driven projects within banking, collaborating with engineering and business teams to gather, translate requirements, and ensure effective delivery of software solutions.
Own Target’s AI-driven agentic experiences, shaping how guests interact with digital channels through intelligent, connected solutions built with cross-functional teams.
The analyst-developer will build quality evaluation systems for LLMs and agent models, including developing LLM-as-a-judge frameworks and data pipelines for Alice. The role involves creating end-to-end metrics and integrating analytical solutions into production environments using Python, SQL, and Pandas.
Build and scale data/AI-driven software solutions using Python/JavaScript, modern frameworks, and cloud tools while collaborating with cross-functional teams.
Design and build AI/ML solutions for chemical and manufacturing clients, including time-series models, anomaly detection, and generative AI systems, deployed on cloud platforms.
The Lead Data Analyst will collaborate with business stakeholders to develop AI-driven analytical solutions and data products that optimize merchandising, supply chain, and marketing strategies. The role involves working with large-scale datasets using GCP, Spark, and SQL to deliver actionable insights and decision-support models.
Builds and deploys AI-powered solutions for customers, integrating models into cloud environments and supporting production systems.
Builds and deploys AI-powered educational tools using large language models and generative AI to serve millions of students across Brazil.
This faculty position at Stanford University involves conducting research at the intersection of AI and biomedical science, including drug design, clinical care improvement, and the development of novel AI methods for health data.
Designs, maintains, and optimizes hybrid on-premise/cloud HPC platforms for scientific/AI workloads, focusing on Linux infrastructure, job scheduling, and automation to ensure high availability and performance.
Analytics Engineer responsible for data transformation, developing analytical models, and implementing data quality frameworks using SQL, dbt, BigQuery, and Python to provide reliable business insights.
Sell Google Cloud’s security and AI solutions to SMBs, acting as a trusted advisor to help customers adopt and expand their use of these technologies.
The Solutions Architect for Data Cloud designs and prototypes reference architectures and technical assets for Google Cloud, focusing on databases, analytics, and GenAI. This role bridges engineering and field teams to solve complex customer data challenges and drive product innovation.
The Data Analyst will join Sber's B2C team to develop recommendation systems and AI agents by analyzing customer journeys, conducting A/B tests, and optimizing business metrics. The role requires expertise in SQL, Python, and product analytics to translate business requirements into technical solutions for AI-driven banking products.
The DevOps Engineer will design, deploy, and maintain infrastructure for scalable AI inference workloads, focusing on Kubernetes, GPU scheduling, and monitoring. The role involves collaborating with ML engineers to build robust CI/CD pipelines and observability tools for on-premises environments.
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