HSBC Group

Business: Corp & Inst Banking
Open positions:1
Role Title: Senior Quant Dev
Global Career Band: 5
Location (Country / City ): India/Bangalore
Recruiter Name : Hariharasudhan G
What you’ll do: 
Model Development & Engineering:

• Design and Develop LLMs: Build, train, and fine-tune LLMs and generative AI models for real-world applications, focusing on tasks such as document understanding, information extraction, question answering, and multimodal representation learning.
• State-of-the-Art Research: Stay at the forefront of AI advancements, particularly in NLP, multimodal learning, and generative AI. Research and implement novel techniques to improve model performance and scalability.
• Model Deployment: Collaborate with engineering teams to deploy models into production environments, ensuring seamless integration with existing systems and processes.
• MLOps Practices: Contribute to the development of MLOps toolkits to streamline the machine learning lifecycle, from model training to monitoring and maintenance.
  Model Validation & Governance:
• Define Validation Metrics: Develop robust metrics and frameworks to evaluate model accuracy, reliability, and robustness, particularly for LLMs.
  Conduct Validation Assessments: Perform rigorous testing, including regression analysis, unit testing, and performance benchmarking, to ensure models meet business and regulatory standards.
• Explore and Establish LLMs as Judges: Develop and implement methodologies for using LLMs as evaluators to assess the quality and accuracy of other AI models, particularly in tasks like natural language processing and document understanding.
• Documentation & Reporting: Maintain detailed documentation of model development, validation processes, and performance metrics to support AI governance and regulatory filings.
• Collaborate with Governance Teams: Work closely with internal compliance and governance teams to ensure models adhere to organizational policies and regulatory requirements.
   

What you will need to succeed in the role: 

• Bachelor’s, Master’s, or Doctorate degree in Machine Learning, Natural Language Processing (NLP), Computer Science, Data Science, Statistics, or a related field.
  Technical Expertise:
• Hands-on Experience with LLMs: Strong expertise in developing, fine-tuning, and deploying LLMs and generative AI models.
• Programming Skills: Proficiency in Python, with experience in libraries such as PyTorch, TensorFlow, Hugging Face Transformers, and tools like LangChain or LlamaIndex.
• NLP & Multimodal Learning: Deep understanding of NLP techniques, multimodal representation learning, and document intelligence (e.g., document classification, information extraction, layout analysis).
• Validation & Testing: Familiarity with unit testing frameworks, performance testing tools, and statistical methods for model evaluation.
• MLOps Knowledge: Understanding of machine learning lifecycle management, model monitoring, and deployment pipelines.
  Experience:
• Proven experience in both developing and validating AI/ML models, particularly in the context of LLMs.
• Experience with document understanding, generative AI, or multimodal models is a plus.
• Ability to work independently and collaboratively in a fast-paced, global environment.
  Soft Skills:
• Strong analytical thinking and problem-solving skills.
• Attention to detail and excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Ability to work under pressure, prioritize tasks, and deliver results in a dynamic environment.
  Experience:
• Proven experience in both developing and validating AI/ML models, particularly in the context of LLMs.
• Experience with document understanding, generative AI, or multimodal models is a plus.
• Ability to work independently and collaboratively in a fast-paced, global environment.
  What additional skills will be good to have?
  Cross-Functional Collaboration:
• Partner with data scientists, engineers, and business stakeholders to align model development with business objectives.
• Collaborate with testing engineers to design and execute test cases, ensuring model accuracy and reliability.
• Provide technical guidance and insights to non-technical stakeholders to facilitate informed decision-making.
  Within HSBC certain roles are designated as Enhanced Vetting Roles. For these roles, all internal and external applicants are required (subject to local laws), to pass satisfactorily a series of additional checks both as part of the application process and, if successfully recruited into the role, on an ongoing basis if they remain in such a role. This role has been designated as an Enhanced Vetting Role.

Link to Candidate User Guide:
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You’ll achieve more at HSBC 
HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.” 
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