Python, Gen AI, AWS, Microservices / Consultant Specialist

Some careers shine brighter than others

If you’re looking for a career that will help you stand out, join HSBC, and fulfil your potential Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further

HSBC is one of the largest banking and financial services organizations in the world, with operations in 64 countries and territories We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realize their ambitions

We are currently seeking an experienced professional to join our team in the role of Consultant Specialist

Design, develop, and fine-tune Generative AI models (, GPT, BERT, Stable Diffusion, etc.) for various use cases such as text generation, summarization, image generation, and more.

Build and deploy scalable AI / ML pipelines using Python and frameworks like TensorFlow, PyTorch, or Hugging Face.

Integrate Generative AI models into production systems and APIs for real-time or batch processing.

Collaborate with cross-functional teams to identify AI use cases and deliver end-to-end solutions.

Optimize model performance, reduce latency, and ensure scalability for production environments.

Conduct research and stay updated on the latest advancements in Generative AI and machine learning.

Work with large datasets, preprocess data, and ensure data quality for training and evaluation.

Implement monitoring and logging for deployed AI models to ensure reliability and performance.

Write clean, maintainable, and well-documented Python code for AI / ML projects.

Requirements

To be successful in this role, you should meet the following requirements :

Experience with fine-tuning and deploying Large Language Models (LLMs) like OpenAI GPT, Google T5, or similar.

Knowledge of Natural Language Processing (NLP) techniques such as tokenization, embeddings, and transformers.

Familiarity with MLOps tools and practices for model deployment, monitoring, and lifecycle management.

Experience with containerization tools like Docker and orchestration platforms like Kubernetes.

Understanding of ethical AI practices and bias mitigation in Generative AI models.

Experience in AWS / Cloud Technologies

Experience with banking systems

Familiarity with AGILE and Scaled AGILE methodologies

Strong proficiency in Python and experience with AI / ML libraries such as TensorFlow, PyTorch, or Hugging Face

Hands-on experience with Generative AI models like GPT, BERT, DALL-E, or Stable Diffusion.

Solid understanding of machine learning concepts, including supervised, unsupervised, and reinforcement learning

Experience with data preprocessing, feature engineering, and working with large datasets.

Experience in building and deploying RESTful APIs or microservices for AI / ML models.

Strong analytical and problem-solving skills with the ability to debug and optimize AI models.

Excellent verbal and written communication skills to collaborate with technical and non-technical stakeholders.