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Build and maintain secure, scalable APIs on Kubernetes that wrap AI services (Databricks, Azure OpenAI, AWS Bedrock) for regulated insurance use cases, enforcing compliance, auditability, and real-time streaming outputs.
Build large-scale predictive models and MLOps pipelines for Fortune 500 clients using Python, SQL, Snowflake, Databricks, and SageMaker.
Manger Data Engineer Department: Data & AnalyticsReports To: Director, Data EngineeringLocation: Remote (U.S.) Position Summary Penn Foster Group is seeking an experienced Lead Data Engineer to help shape the…
Build and maintain ML data pipelines for autonomous trucking, curating high-quality sensor annotations and delivering on-demand training data to perception models.
Build and deploy ML models for 3D scene reconstruction, lane detection, and HD map creation using LiDAR/camera data to generate high-quality annotations for autonomous trucking systems.
Builds and deploys GenAI applications using LLMs, fine-tuning models, and integrating MLOps pipelines for production systems like chatbots and document analyzers.
Build and operate production-grade ML pipelines on Databricks, implementing MLOps practices like CI/CD, model monitoring, and secure deployment while collaborating with data science and engineering teams.
Build and deploy ML models, predictive analytics, and optimization algorithms to solve business problems across DKSH’s supply chain and markets, using Python, SQL, and cloud platforms.
Lead AI/ML engineering for medical imaging: build, evaluate, and deploy deep-learning models for segmentation, detection, and classification across dental radiographs and CBCT data.
Build and deploy AI models using Python, TensorFlow/PyTorch, and MLOps on Azure to drive predictive analytics and business insights.
Build and deploy AI models using Python, TensorFlow/PyTorch to generate business insights and predictive analytics, collaborating with cross-functional teams.
Embed within client teams to design and deploy scalable data platforms, ML pipelines, and GenAI workflows using Python, Spark, and cloud-native tools.
Build and optimize generative AI systems, focusing on RAG pipelines, LLM evaluation, and enterprise-scale deployments to improve retrieval quality and reduce hallucinations.
Build and maintain enterprise-grade communication surveillance apps for a bank using Java/Spring Boot, React, Node.js, and cloud tools; integrate AI/ML for detecting compliance breaches across emails, chats, and voice transcripts.
Build and run Absa’s multi-cloud AI platform, deploying and scaling services on AWS Bedrock, Databricks, Azure AI Foundry, Hugging Face, and Kubernetes to power enterprise AI use cases across the bank.
Design and run Absa’s multi-cloud AI platform (AWS Bedrock, Databricks, Azure AI Foundry) that powers 43 live AI projects across ten African countries, focusing on FinOps, zero-trust security, and agentic AI infrastructure.
Build cloud-native Python services and APIs that power data-driven network analytics, forecasting, and AI at a major media and entertainment company.
Principal AI Data Engineer builds and deploys GenAI, RAG and agentic AI prototypes using Azure AI Foundry, Databricks Mosaic AI and LangChain on Azure cloud.
Build and maintain ML pipelines on Azure and Databricks, deploy models, and set up MLOps processes for a higher-education group.
Build and automate end-to-end ML pipelines for retail analytics and forecasting, integrating Oracle, Snowflake, and AWS with Kedro, MLflow, and Docker.
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