AI Data Engineer in Singapore designing and owning end-to-end AI-driven data pipelines on AWS (Bedrock) for corporate secretarial and accounting document processing. Day to day: fine-tuning and deploying ML models, building multimodal pipelines, and applying MLOps practices with Python, ETL/ELT, and AWS services.
It's never been a more exciting time to join Vistra.
At Vistra our purpose is progress. We believe that our clients have the power to change the world and to do great things for global progress, and we exist to remove the friction that comes from the complexity of global business – to help our clients achieve progress without friction.
But progress only happens when people come together and take action. And we're absolutely committed to building a culture where our people can do just that.
We are seeking a highly skilled and motivated
AI
Data Engineer
to join our dynamic and innovative team. Reporting to the Engineering Lead, this full-time and permanent position is based in Singapore.
The ideal candidate will have approximately 5-7 years of hands-on experience, ideally working on AI products or related initiatives.
This role requires a proven ability to collaborate with stakeholders, analyse complex data requirements, and deliver cutting-edge solutions in a fast-paced environment. Familiarity with AWS Bedrock is essential, as you will be leading the design and implementation of AI-driven data pipelines on AWS.
Key Responsibilities:
Fine-tune and deploy machine learning models from initial research to production, ensuring scalability and performance for data extraction, parsing, and prediction in corporate secretarial and accounting use cases.
Distil large model behaviors to smaller custom designed multimodal models jointly processing image + text and train them manually.
Hand-design custom AI pipelines comprising of various model types like neural nets, decision trees, rule-based systems working together to achieve a common goal.
Mathematical Innovation for novel AI techniques - we welcome original and first-principles thinking. You will be encouraged to ideate out-of-box fundamental scientific solutions and given bandwidth to experiment.
Own the end-to-end ML pipeline (data processing, model fine-tuning, testing, deployment, and continuous optimization), implementing MLOps best practices for reliability and scalability.
Architect, build, and maintain AI-driven data pipelines for structured and unstructured document processing using AWS Bedrock and other AWS services, ensuring data governance, security, and quality across the data lifecycle.
Evaluate and implement AI-driven automation solutions to streamline corporate compliance workflows, ensuring adherence to regulatory requirements in corporate secretarial and accounting processes.
Collaborate with cross-functional teams to gather requirements, perform feature engineering, model tuning, and code reviews, ensuring production-ready solutions.
Implement and maintain data governance, data security, and data quality measures throughout the data lifecycle.
Work closely with engineering teams to integrate AI-driven functionalities into our products.
Participate in code reviews and provide technical expertise to ensure best practices in AI/data engineering.
Continuously research and evaluate emerging AI and data technologies to enhance solutions, tools, and processes, driving business value and innovation.
Key Requirements:
Bachelor's degree in Computer Science, Engineering, or a related field.
Approximately 5-7 years of experience in AI/data engineering roles.
Proficiency in one or more programming languages commonly used in AI/data engineering (e.g. Python, Node.js).
Strong knowledge of ETL/ELT processes, data warehousing concepts, and data pipeline orchestration.
Versed in mathematical foundations of training AI models from scratch (loss function surgery, convex optimization, attention blocks, convolution neural nets). Solid fundamental mathematical understanding of the transformer core architecture and its training.
Practical experience with machine learning model development, including model training, tuning, and deployment.
Familiarity with REST APIs or GraphQL endpoints.
Experience working in Scrum Agile software engineering teams.
Excellent problem-solving, analytical, and communication skills.
Bonus Experience:
Experience with Next.js and TypeScript.
Experience with RLHF (Reinforcement Learning with Human Feedback).
Familiarity with Terraform or other Infrastructure as Code (IaC) tools.
Exposure to large language models or generative AI techniques.
Experience with advanced data visualization tools or analytics platforms.
Company Benefits:
At our Singapore office, we believe in putting our employees' well-being first! We offer a flexible hybrid working arrangement.
Additionally, we provide comprehensive medical insurance and dental coverage, wellness allowance and competitive annual leave entitlement to support your well-being and time to recharge or explore your passions out of work.