AI Engineer/Senior Software Engineer/Pune/Global Ops

2 weeks ago

Pune, Maharashtra, India HSBC Full time

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 organisations 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 realise their ambitions.

We are currently seeking an experienced professional to join our team in the role of : Senior Software Engineer

In this role, you will

We are seeking an experienced AI Engineer who will be responsible for developing and implementing artificial intelligence models and strategies for our organization. The successful candidate will have an in-depth understanding of machine learning techniques, data structures, data modeling and software architectur Solutioning Experience: Experience in architecture and design, translating business requirements into technical specifications, and developing scalable and robust AI solutions. Prior development of a large software project using service-oriented architecture operating with real time constraints. Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Technical Skills: Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Cloud Experience: Familiarity with cloud platforms (, Azure, AWS, GCP) and related services Experience in full AI project lifecycle, from research and prototyping to deployment in production environments. (preferably Azure) Experience with version control systems, particularly Git, and proficiency with GitHub for code collaboration and repository management. Experience in working with SQL/NoSQL database systems such as MySQL, MongoDB or Elasticsearch. Good understanding of distributed systems, understanding of microservice architecture and REST APIs. Excellent knowledge and working experience with Docker containers. Consistent track record in developing large scale distributed applications. Experience with transformer-based and diffuser-based models (, BERT, GPT, T5, Llama, Stable diffusion) Proficiency in Agile development practices and Continuous Integration/Continuous Deployment (CI/CD) Preferred training & fine-tuning experience on large data Work closely with data engineers and data analysts to help build ML- and statistics-driven data quality and continuous data monitoring workflows. Awareness and understanding of ethical considerations in data science and AI, ensuring responsible and fair use of data and AI technologies. Own the MLOps lifecycle, from data monitoring to refactoring data science code to building robust model monitoring workflows for model lifecycle management. Requirements

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

Total 5+ years of relevant experience Education: Degree in Computer Science, Mathematics, Engineering, or a related field. Business Acumen: Ability to understand customer needs and business objectives. Experience in working closely with customers and translating their requirements into effective AI solutions. Customer Engagement and Support: Act as a technical point of contact for customers, addressing their questions, concerns, and feedback. Provide technical support during the solution deployment phase and offer guidance on AI-related best practices and use cases. Documentation and Knowledge Sharing: Document solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Preferably JIRA Confluence Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Industry Trends and Innovation: Stay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation.

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