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The Data Engineer will design and implement data pipelines to transform raw robot and external datasets into structured, reproducible formats for training AI models. The role focuses on building validation suites, managing dataset versions, and creating tools to support ML teams in the robotics center.
Build and deploy AI/ML and NLP models, including LLMs, to automate healthcare workflows while ensuring clinical accuracy, regulatory compliance, and production reliability.
Develop AI, GenAI and Agentic AI prototypes using Azure, Databricks, and LangChain for a Trading & Supply team. Responsibilities include building RAG solutions, deploying agents, and managing scalable AI workflows with Python and SQL.
Senior Data & AI Engineer / MLOps Engineer productivizing AI solutions, responsible for ML model lifecycle, data pipelines, and production deployment using Python, PySpark, SQL, AWS, Docker, Kubernetes, CI/CD, Git, and MLflow.
Product Manager owning the end-to-end product data ecosystem, ML evaluation frameworks, and A/B testing strategies for AI-driven enterprise products, working cross-functionally with Engineering and Data Science teams.
An AI/ML Engineer at Nexstar Media Group designs, builds, and deploys machine learning and agentic AI systems for real-world products, working across the full ML lifecycle from data preparation to model monitoring and iteration.
Junior MLOps Engineer responsible for automating ML pipelines (CI/CD for ML), deploying models to production using Kubeflow and MLflow, and monitoring data drift and model performance. Core technologies include Python, Docker, Kubernetes, Kubeflow, and MLflow.
Principal Data Scientist builds and deploys ML models to drive credit decisions and financial progress for customers, using PyData tools and production-grade pipelines.
Senior Data Scientist builds and deploys machine learning models to make lending decisions for a fintech company, using Python and PyData tools.
Kroll is hiring a Data Science Manager to lead and grow our data science function within the Enterprise Data Group. This role sits at the intersection of technical leadership and strategic delivery — you will shape how…
Senior Data Scientist designs and deploys ML models (traditional, deep learning, NLP, LLM/GenAI) on Azure/Databricks to solve fintech risk and compliance challenges.
Builds and deploys ML models (traditional, NLP, GenAI) for fintech/government clients, focusing on data pipelines, feature engineering, and model monitoring in Databricks/Azure.
Designs and builds scalable cloud-native AI/ML and GenAI infrastructure for Toyota Financial Services, focusing on MLOps/LLMOps, GPU-accelerated compute, and secure model deployment at enterprise scale.
Lead the design, development, and deployment of AI/ML-powered applications and microservices on Kubernetes, using MLOps/AIOps tools and cloud platforms to deliver scalable, production-grade solutions.
Build and deploy machine learning models and services, focusing on MLOps practices, API development, and cloud infrastructure using Python, AWS, and tools like MLflow and Databricks.
Designs and implements AI-native security architecture for an AI-first enterprise platform, securing GenAI agents, models, and integrations while building ML-driven threat detection and autonomous security agents to analyze 22B+ monthly security events across 176K+ hosts and 266+ Kubernetes clusters.
Leads AI architecture and development of agentic/Generative AI systems, including LLM-powered agents, RAG pipelines, and multi-agent workflows, while mentoring engineers and collaborating cross-functionally to deliver scalable, production-grade solutions.
Own and evolve an internal AI platform, collaborating with data and engineering teams to enable scalable AI solutions through backlog management, stakeholder alignment, and Agile delivery.
Develops AI/ML-driven analytics and data pipelines to strengthen IAM controls, governance, and risk reduction in fintech. Focuses on access anomaly detection, entitlement mining, and control effectiveness using Python, R, SQL, Neo4j, and Tableau.
Design and implement AI models for aquaculture using computer vision and deep learning to analyze aquatic species traits from imaging data.
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