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Establish MLOps practices and productionize machine learning models within the Databricks ecosystem, defining how models are built, tracked, deployed, and monitored in collaboration with data science teams.
Leads AI/ML engineering initiatives, designing and deploying enterprise-scale LLM and RAG applications while defining technical architecture and driving cross-functional delivery for business impact.
The Data Engineer will design and maintain cloud-based data pipelines and infrastructure to support predictive maintenance and sensor-based analytics for aviation products. The role involves working with data science teams to implement MLOps, data models, and AI-driven tools using technologies like Azure, Python, and Databricks.
The Senior Manager, AI & Data Engineering leads teams in building and operating governed data products and AI-ready platforms to support enterprise analytics and decision-making. This role oversees strategy and execution for cloud-native data ecosystems using AWS technologies to drive business outcomes.
Develops and deploys AI/Gen AI solutions for corporate functions, focusing on agentic architectures, prompt engineering, and model integration while ensuring Responsible AI compliance and data governance.
Builds production-grade AI/Generative AI solutions (LLMs, RAG, agentic workflows) by designing Python microservices, APIs, and cloud-integrated systems for Thermo Fisher’s scientific and healthcare applications.
Data Scientist building and maintaining enterprise AI infrastructure—agentic AI frameworks, low-latency LLM inference stacks, and MLOps/DevOps pipelines—primarily on AWS for OCBC Bank in Singapore.
The Consultant, Scrum Master will lead Agile delivery practices for the Annuity Modernization Program, coaching teams on Scrum principles and facilitating cross-team planning. This role requires extensive experience in large-scale technology environments and proficiency with Jira to drive value-based delivery and continuous improvement.
Senior data scientist building and deploying AI/ML and GenAI solutions for social impact, from design to production, using Python and full-stack engineering.
Become a part of our caring community The Senior Software Engineer codes software applications based on business requirements. The Senior Software Engineer work assignments involve moderately complex to complex issues…
OUR VISION EQUS is building the trust infrastructure for personal AI. Our product suite spans a personal AI assistant, a personal data store with per-file, user-controlled access, and a developer toolkit for agent…
SAIC is seeking an experienced AI/ML Engineer to serve as a senior technical advisor, ensuring infrastructure supports frontier AI models, mission use cases, and rapid R&D experimentation. Support model-agnostic…
Consultant Machine Learning & Knowledge Graph Engineer Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic…
By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice…
Məlumat bazası üzrə mühəndis Vakansiya haqqında Şirkət : Azerconnect Group İdarə : Rəqəmsallaşma və Data İdarəsi İş qrafiki : Həftənin 5 günü saat 09:00-dan 18:00-dək. Son müraciət tarixi : 11.09.2026 İKT və yüksək…
About us Looking for your next challenge? Allfunds (AMS: ALLFG) is a fast-paced, dynamic, Wealthtech leader with 17* offices around the globe and our employees are the best at what they do. We have a relentless passion…
Job Description WHAT IS THE OPPORTUNITY? Are you a talented, creative and results-driven professional who thrives on delivering high-performing applications? Come join us! Global Functions Technology (GFT) is part of…
The Data Scientist will build and maintain enterprise-grade AI platform components, focusing on MLOps, LLM orchestration, and infrastructure provisioning using tools like Kubernetes, Terraform, and AWS services. They are responsible for the full lifecycle of model deployment, monitoring, and optimization within the bank's data office.
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