Top AI & Machine Learning Jobs

Designs enterprise data architectures, data models, modern data platforms, governance capabilities, and high-value data products for financial institution clients. Partners with technical and business stakeholders to translate complex challenges into scalable solutions, supports cloud migration and data transformation initiatives, contributes to Agile delivery, mentors colleagues, and helps grow the consulting practice.

Build and deploy production-grade AI solutions for financial services, including multi-agent workflows, LLM and neural network applications, RAG systems, data pipelines, and automation tools. Collaborate with technical and business stakeholders, fine-tune models, monitor production systems, and ensure regulatory, privacy, ethical AI, and scalability requirements are met. Participate in code reviews, agile ceremonies, and CI/CD processes.

Design, develop, integrate, test, deploy, and monitor secure AI solutions for banking use cases. Translate business requirements into technical architectures and production capabilities, including Generative AI and Agentic AI applications. Implement responsible AI controls such as access management, logging, explainability, auditability, privacy, human oversight, and reproducibility. Collaborate with business, product, data, risk, technology, and client stakeholders in regulated environments.

Lead hands-on optimization of fraud machine learning models, ML pipelines, and Google Cloud infrastructure. Improve performance, reliability, resilience, and operating costs across compute, storage, networking, training, inference, and distributed data workloads. Provide implementation-ready code and configuration guidance, estimate savings and effort, and apply software engineering practices including Python, SQL, CI/CD, testing, and code review. Collaborate with infrastructure, data science, and business stakeholders while using AI tools responsibly in regulated environments.

Lead AI-driven data and analytics programmes in financial services, mentoring teams and ensuring delivery of measurable outcomes.

Lead and mentor data science teams to design, develop, and deploy ML and AI solutions (including GenAI/LLMs). Align technical outcomes with business goals, drive MLOps and model governance, and deliver scalable production systems.

Design, build, test, and deploy AI-enabled applications for financial services using LLMs, RAG, semantic search, embeddings, and agentic patterns. Integrate with data platforms, ensure scalability, reliability, monitoring, and governance, and collaborate with stakeholders to deliver production-ready, explainable AI solutions.

As a Data Analytics Principal Consultant, you'll lead data transformation initiatives, mentor consultants, and engage with stakeholders in financial services to drive data literacy and innovation.

Design, build, and deploy production-grade AI applications using LLMs, RAG, and agent architectures. Implement vector-database-backed retrieval solutions, create scalable REST APIs and cloud-native backends, and collaborate with cross-functional teams to translate business requirements into robust AI solutions following engineering best practices.

Build end-to-end machine learning and GenAI solutions for regulated financial services clients. Responsibilities include developing scalable data pipelines, training and validating ML models, creating RAG and agentic LLM workflows, deploying and monitoring production models, detecting drift, managing releases, and collaborating with compliance and engineering stakeholders on documentation and knowledge transfer.