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Industry/Sector Not Applicable Specialism Data Science Management Level Associate Job Description & Summary The Opportunity As an AI Engineer- Experienced Associate- Commercial Technology & Innovation, you will…
Industry/Sector Not Applicable Specialism Data Science Management Level Manager Job Description & Summary The Opportunity As an AI Engineer- Manager- Commercial Technology & Innovation, you will play a pivotal…
RELOCATION ASSISTANCE: Relocation assistance may be available CLEARANCE REQUIRED FOR START: Yes CLEARANCE TYPE: Top Secret TRAVEL: Yes, 10% of the Time Description At Northrop Grumman, our employees have incredible…
Builds AI-assisted automation workflows and integrations (e.g., n8n, APIs) to connect disparate systems for clients and internal ops, focusing on practical solutions and operational efficiency.
Builds and maintains data pipelines, automates workflows, and develops AI/ML services using best practices in data engineering and version control.
Develop and maintain AI microservices, debug issues, and optimize code for scalability while collaborating with cross-functional teams.
Build and deploy AI/ML prototypes and integrations to automate workflows for finance and shared-service teams using Python, LLMs, and cloud APIs.
Build and deploy AI agents using Python, LangChain/LlamaIndex, and vector databases with OpenAI/Azure OpenAI APIs.
Build, test, and deploy AI-powered applications and machine learning solutions while learning cloud platforms and responsible AI practices alongside senior engineers.
Build, deploy and operate AI and Generative AI solutions (agents, RAG systems, predictive models) end-to-end, including data pipelines and integrations, using Python, Azure AI, Databricks and related tools.
Build and deploy AI/ML models, including generative AI and LLM-based apps, using frameworks like GPT or open-source models, and design RAG pipelines with vector databases.
Build and deploy AI-powered applications and data pipelines under mentorship, working with cloud platforms, Python, and modern AI frameworks to solve business challenges.
Builds agent-based AI software using foundation models and modern engineering practices to create intelligent, autonomous systems.
Build and test AI agents and integrations for banking workflows using Python/JavaScript, guided by senior engineers to automate processes and improve software development.
Build and maintain data pipelines, cloud infrastructure, and AI models in Python/SQL while learning on real client projects with mentorship.
Build and deploy production-grade AI/ML services for Mastercard’s payments systems, collaborating with data scientists and engineers to ship reliable, scalable features.
Build and optimize AI models (RAG) to solve financial-services problems, collaborating with teams to integrate solutions and analyze data using Python/TensorFlow.
Build and deploy AI models to optimize logistics and digital services, collaborating with data scientists and ML engineers using MLOps practices.
Build, test, and deploy AI/ML models; preprocess data and help fine-tune models for Translation Empire’s AI-driven applications.
Build and deploy production AI systems, including LLM-powered chatbots and RAG pipelines, using Python/Node.js and cloud infrastructure.
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