Graduate Software Engineer - AI & Machine Learning

About the Role

We invite enthusiastic recent graduates to join our AI & Machine Learning Engineering team supporting a premier global Wealth Management client. This position provides a unique chance to engage with cutting-edge Artificial Intelligence, Machine Learning, and Generative AI technologies that redefine interactions between financial entities and their data and clients.

As a member of the AI/ML team, you will aid in designing, developing, and deploying innovative AI capabilities encompassing Natural Language Processing (NLP), Semantic Search, Retrieval-Augmented Generation (RAG), Agentic AI, MLOps, and Foundation Models powered by exclusive enterprise datasets.

Comprehensive training will be offered, and you will collaborate closely with skilled AI engineers, data scientists, and domain specialists to develop robust AI solutions tailored to Wealth Management use scenarios.

Primary Responsibilities

• Design, create, and implement Machine Learning and Deep Learning algorithms for practical business issues.
• Develop and improve NLP systems including Semantic Search and intelligent knowledge retrieval mechanisms.
• Build and refine Retrieval-Augmented Generation applications using enterprise knowledge bases.
• Contribute to the formulation of Foundation Models and Large Language Models leveraging proprietary corporate data.
• Create and advance Agentic AI applications with modern AI orchestration frameworks.
• Engage in development of Model Context Protocol integrations and related AI services.
• Support scalable MLOps pipelines for AI model deployment, supervision, and lifecycle management.
• Work collaboratively with data scientists, software engineers, and business teams to deliver AI-enhanced products and solutions.
• Analyze complex data sets and devise solutions based on data-driven insights.
• Participate in model testing, performance tuning, evaluation, and iterative improvement efforts.
• Contribute to AI governance, responsible AI use, and ensuring model dependability.

Essential Skills

• Proficiency in Python programming and data engineering techniques.
• Experience with SQL and working knowledge of data structures and algorithms.
• Familiarity with data handling libraries such as Pandas and NumPy.
• Knowledge of Machine Learning paradigms including supervised and unsupervised learning.
• Understanding of Deep Learning architectures and Neural Networks.
• Expertise in Natural Language Processing, Transformers, and Large Language Models.
• Experience or interest in Retrieval-Augmented Generation and Agentic AI techniques.
• Familiarity with Model Context Protocol, Prompt Engineering, and AI evaluation methodologies.
• Working knowledge of cloud-related tools such as Git, CI/CD workflows, Docker; Kubernetes familiarity is advantageous.
• Understanding of ML model deployment, monitoring, and MLOps concepts.

Eligibility Criteria

• The candidate should hold a Bachelor's degree in Computer Science, AI, Data Science, Computer Engineering, IT, Mathematics, Statistics, or closely related areas.
• Applicants must be fresh graduates or possess up to two years of relevant experience.
• They should demonstrate a strong academic foundation and enthusiasm for AI, ML, and innovative technologies.
• Excellent analytical thinking, problem-solving capabilities, and communication skills are essential.
• Candidates should be eager to learn and thrive in a dynamic, cooperative work environment.