AI Engineer at Vistra fine-tuning and deploying machine learning models for corporate compliance solutions. Collaborating with cross-functional teams to innovate and drive business value using AI technologies.
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.
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.
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.
Benefits
flexible hybrid working arrangement
birthday leave
comprehensive medical insurance and dental coverage
wellness allowance
competitive annual leave entitlement
internal mentorship program
reimbursement of professional membership fees for certifications like CA, or ACCA
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