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Design and deploy a secure, on-premises AI platform in a classified environment, building scalable HPC infrastructure and DevSecOps ecosystems for mission-critical defense programs.
Build and analyze marketing data models in Python/SQL/R to optimize ad campaigns and inform business decisions for a global media agency.
Build and deploy AI/ML models, generative AI, and intelligent automation solutions to improve payments and financial services at a global fintech leader.
Design and modernise a cloud-based data platform for a large online gambling operator, focusing on lakehouse architectures, Spark pipelines, and AI-driven personalisation while ensuring regulatory compliance.
Build and maintain scalable data pipelines for space-domain simulations, integrating multi-classification data sources using Python, SQL, and ETL tools to support mission-critical modeling.
Senior AI Engineer builds and deploys scalable machine-learning and LLM-powered solutions to transform products and operations, focusing on generative AI, retrieval-augmented generation, and cloud platforms.
Builds and deploys ML and LLM models to improve business decisions, creates Power BI dashboards, and partners with stakeholders to scale AI solutions in an education-focused company.
Lead a team building cloud-native, multi-cloud data platforms for GM’s connected services, marketing, and AI products using Databricks, Spark, and real-time streaming.
Build and maintain cloud data platforms (Snowflake, Microsoft Fabric, Databricks) and BI tools (Power BI, Tableau) while supporting AI/ML enablement and accounting-focused analytics for a top accounting and consulting firm.
Senior engineer building and running cloud data platforms (Snowflake, Fabric, Databricks) and BI tools (Power BI, Tableau) for a top accounting and consulting firm, owning reliability, CI/CD, security, and governance.
Build and maintain ML infrastructure and data pipelines to operationalize AI models for drug-quality oversight in a regulated healthcare environment, using Python, cloud platforms, and MLOps practices.
Working with Us Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens…
Lead Engineer builds and deploys production-grade AI/ML models and inference pipelines for retail and operations use cases using Python, PyTorch/TensorFlow, and cloud ML tooling.
Build and maintain ML and data infrastructure to operationalize AI models for drug quality oversight, enabling proactive risk detection and compliance in a regulated healthcare environment.
Build and deploy scalable AI/ML solutions using LLMs and orchestration frameworks in Python, applying MLOps best practices in a large, data-driven organization.
Design and scale an enterprise AI platform using Red Hat OpenShift and OpenShift AI, focusing on container-native MLOps, LLM serving, and automated benchmarking for production deployments.
Build and maintain the MLOps infrastructure that deploys and monitors Autodesk’s AI/ML models, automating pipelines with Kubernetes, Terraform, and CI/CD while enforcing security and governance.
Build and deploy ML models to detect debit fraud in real time, using Python, Spark, and gradient boosting, while collaborating with engineers and product teams to protect customers.
Build and optimize machine learning models for time-series forecasting and predictive analytics using Python, PySpark, and SQL to drive business value in healthcare logistics.
Coach Agile teams at a Fortune 100 insurer, removing blockers and guiding Scrum/Kanban practices to deliver secure software solutions that protect customer data.
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