Why This Role Stands Out
This hybrid AI Engineer role at MetaRPO offers a fantastic opportunity to develop cutting-edge AI solutions for the dynamic banking and financial services sector, leveraging your expertise in Python, Machine Learning, and Generative AI. You'll thrive in this collaborative environment if you're passionate about building scalable, secure AI applications and contributing to impactful projects that drive innovation. Apply now to advance your career with a forward-thinking company!
Quick Overview
Job Description
Job Description
We are looking for an experienced AI Engineer to design, develop, deploy, and maintain AI/ML solutions for the Banking and Financial Services domain. The ideal candidate will have strong hands-on experience in Python, Machine Learning, Generative AI, Large Language Models (LLMs), and cloud platforms, with a good understanding of banking and financial applications.
The candidate will work closely with data scientists, software engineers, architects, and business stakeholders to build secure, scalable, and production-ready AI solutions.
Key Responsibilities
- Design, develop, and deploy AI/ML models and applications for banking and financial services.
- Develop AI solutions using Python, Machine Learning, Deep Learning, and Generative AI.
- Build and integrate LLM-based applications, AI agents, and Retrieval-Augmented Generation (RAG) solutions.
- Develop APIs and services to integrate AI solutions with existing banking applications.
- Work with structured and unstructured financial data to identify patterns and generate insights.
- Develop AI solutions for use cases such as fraud detection, credit risk, loan processing, customer service, document processing, and financial analytics.
- Implement model evaluation, monitoring, optimization, and performance improvements.
- Work with cloud-based AI/ML services and deploy models into production environments.
- Ensure AI solutions meet banking requirements for security, privacy, compliance, and responsible AI.
- Collaborate with data engineering teams to develop reliable data pipelines for AI/ML applications.
- Participate in code reviews, testing, troubleshooting, and production support.
- Follow Agile/Scrum methodologies and contribute to technical documentation.
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