VP, Machine Learning Architect

Description Overview Join to apply for the VP, Machine Learning Architect role at GIC . GIC is one of the world’s largest sovereign wealth funds. With over 2,000 employees across 11 locations around the world, we invest in more than 40 countries globally across asset classes and businesses. Working at GIC gives you exposure to an extraordinary network of the world’s industry leaders. As a leading global long-term investor, we work at the Point of Impact for Singapore’s financial future, and the communities we invest in worldwide. The Artificial Intelligence Alpha Group (AAG) is a newly formed, AI-native investment team dedicated to using artificial intelligence to drive superior investment performance. We are pioneering a new model of active investing that fuses domain expertise, proprietary data, and cutting-edge generative AI. AAG is a cross-functional team comprising experienced investors and expert technologists, working together to generate differentiated insights and deliver investment outperformance. What impact can you make in the role? We are seeking a Machine Learning Architect to join us as a senior technology specialist. In this role, you will translate complex business requirements into technical solutions and play a key role in the foundational phase of developing next-generation AI-driven research and investing systems. You will work closely with the team leads to define technical roadmaps aligned with strategic objectives and take responsibility for designing and building the system foundation, guiding a cross-functional engineering team, and establishing best practices for delivery and execution. This is a highly hands-on role that combines architecture, data science, engineering, and leadership during the formative stages of the platform. What will you do as a Senior ML Engineer / Architect? Work closely with team leads to shape technical roadmaps that align with strategic priorities. Translate business requirements into detailed technical specifications and system architectures. Drive the integration and processing of proprietary and external datasets, including feature engineering and advanced data modelling for retrieval, training, and evaluation. Drive the development of an end-to-end platform, spanning data ingestion, processing, model workflows, multi-agent orchestration, and user-facing integration. Build and operate infrastructure to support model development, deployment, monitoring, and scaling. Provide technical guidance to a cross-functional team of engineers (data science, data engineering, software development, MLOps, QA). Establish engineering standards for code quality, observability, testing, and documentation. Direct and coordinate the work of external engineering resources, ensuring clear scope definition, assignment, progress tracking, and seamless integration toward delivery. What makes you a successful candidate? 12+ years of experience in software engineering and system architecture, with strong exposure to ML infrastructure and applications. Proven track record of building and delivering large-scale, mission-critical systems. Hands-on expertise with ML pipelines, distributed training, and orchestration frameworks (e.g., PyTorch, HuggingFace, LangChain/LangGraph, vector databases). Strong background in big data architecture, including data ingestion, transformation, feature engineering, and advanced data modeling techniques (e.g. graph databases, knowledge graphs). Broad technical skills spanning full-stack development, backend systems, big data platforms, and DevOps. Familiarity with data science workflows, including model evaluation and applied ML integration. Experience leading cross-functional teams and coordinating external vendors or partners. Strong ability to translate high-level business requirements into robust technical solutions. Relevant experience or training in capital markets or investment research is preferred. Work at the Point of Impact We need to be forward-looking to attract the right people to help us become the Leading Global Long-term Investor. Join our ambitious, agile, and diverse teams - be empowered to push boundaries and pursue innovative ideas, share your views, and be heard. Be anchored on our PRIME Values: Prudence, Respect, Integrity, Merit and Excellence, which guides us in how we make our day-to-day decisions. We strive to inspire. To make an impact. Flexibility at GIC At GIC, our offices are vibrant hubs for ideation, professional growth, and interpersonal connection. At the same time, we believe that flexibility allows us to do our best work and be our best selves. Thus, our teams come into the office four days per week to harness the benefits of in-person collaboration, but have the flexibility to choose which days they work from home and adjust this arrangement as situational needs arise. Equal opportunity GIC is an equal opportunity employer, and we value diversity. We do not discriminate based on race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please email at any point of the application or interview process if adjustments need to be made due to a disability. Our PRIME Values GIC is a values driven organization. GIC’s PRIME Values act as our compass, enabling us to fulfil our fundamental purpose and objectives. PRIME stands for Prudence, Respect, Integrity, Merit and Excellence. Seniority level: Mid-Senior level Employment type: Full-time Job function: General Business, Finance, and Other Industries: Investment Management and Financial Services Referrals increase your chances of interviewing at GIC by 2x We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #J-18808-Ljbffr Industry Other Category IT & Technology Sub Category Software Development