Machine Learning Engineer

The Full Stack Engineering role entails involvement across the Technology delivery life cycle, including inception, construction, testing, release, and ongoing management of a product or service within a Technology team's pod. The ideal candidate will have a solid background in AI and machine learning, as well as experience in software development and engineering, with a particular emphasis on LLM applications. This person will be a key member of the team, bringing the Generative AI solution from concept to production.

Responsibilities:

• Develop and deploy scalable solutions for Generative AI/LLM projects into a production environment, with end-to-end accountability for delivering innovative and effective products that meet stakeholders' and customers' demands.
• Conduct Proof-of-Concept (POC) and prototyping to explore and validate the flexibility of innovative ideas, including prompt engineering.
• Implement data pre-processing and integration pipelines for contextual embedding, with the potential for fine-tuning LLM models.
• Promote the adoption of best practices and introduce high standards of coding quality to the team.
• Collaborate with other engineers, architects, and business stakeholders to understand and drive the product or service's direction.
• Establish a digital environment and automate processes to minimize variation and ensure predictable high-quality code and data.
• Create technical test plans and records, including unit and integration tests, within automated test environments to ensure code quality.
• Improve the performance and accuracy of the Generative AI/LLM system through experimentation, testing, evaluation, and analysis.
• Provide training and support to business users to help them effectively use the Generative AI/LLM solutions.
• Support DevOps teams working at all stages of a product or service release/change, providing excellent customer focus and end-to-end journeys, ensuring they have an excellent domain knowledge.
• Work with Ops, Dev, and Test Engineers to ensure operational issues (performance, operator intervention, alerting, design defect related issues, etc.) are identified and addressed at all stages of a product or service release/change.
• Collaborate with Ops Engineers to resolve operational issues (performance, operator intervention, alerting, design defect related issues, etc.), ensuring that any design-related issues are addressed promptly.
• Support in identifying and resolving all incidents associated with the IT service, as directed by the leadership of the DevOps team.
• Responsible for automating the continuous integration/continuous delivery pipeline within a DevOps Product/Service team, promoting a culture of continuous improvement.
• Stay up-to-date and maintain expertise on current tools, technologies, and areas like cybersecurity and regulations relating to aspects like data privacy, consent, data residency etc.
• Accountable for ensuring the design of the product solutions are cost-effective and maintained throughout the agile development lifecycle, managing the flow of the design activities backlog.

Requirements:

• Minimum 4 years’ hands-on application design or solution architecture experience.
• Full stack software engineering capability, including front-end, middleware, and backend.
• Strong analytical, design, and problem-solving skills, logical and critical thinking, combined with engineering skills to put design into code.
• Business knowledge in the financial services industry is preferred.
• Experience of working in a DevOps-focused environment and working in an Agile Team. Flexible and adaptable in accommodating changes in requirements and willing to take on new responsibilities when necessary.
• Excellent team player who can work under pressure with minimal supervision.
• Ability to quickly set up a PoC environment on the cloud, container, etc.
• Strong engineering hands-on experience with complex enterprise solutions, e.g., design for availability, scalability, operability, resilience, maintainability, and ensure their implementation.
• Familiarity with cloud platforms, with experience on at least one cloud platform among Azure, GCP, AWS, and Ali Cloud.
• Familiarity with programming, database technology, and their relevant design patterns (e.g., Java/Python/Golang/Node.js/relational DB/NOSQL DB).
• Capabilities to use and extend common open frameworks (e.g., Langchain, LlamaIndex, etc.), NLP algorithms/packages (e.g., embedding, word2vec, NLTK, Gensim, spacy, etc.), with knowledge and/or experience on vector database
• Experience managing delivery program over multiple workstreams.
• Experience overseeing technology adoption from conception, design, development, to production.
• Hands-on delivery of digital products in a large enterprise.
• Fluent in speaking Mandarin, Cantonese, and English.
• Proficient in Chinese and English writing.