Base Camp Digital Hiring! Full Time Senior- Tech Lead Machine Learning Engineer (AI Systems) in - Ricebowl

Job Title: Senior/Technical Lead, Machine Learning (AI Systems)
Location: SG (Remote)


About the Company
A well-funded technology company building next-generation AI products for everyday consumers. the mission is to bring intelligent, proactive assistance to the everyday tools people already rely on - messaging, task management, scheduling, and organization - making complex, multi-step tasks feel effortless.



About the Role

We're looking for a Technical Lead, Machine Learning to own the execution layer of our AI product - translating research and model capabilities into robust, scalable, production-grade systems. This role sits at the intersection of applied ML, infrastructure, and product, and is central to how our AI actually performs in the real world, not just in controlled testing.

You'll have full ownership across the ML lifecycle - from data and training pipelines to fine-tuning, evaluation, and production inference - with direct influence on how our core AI systems are built and scaled.



What You'll Own

• End-to-end ML system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment
• Fine-tuning and adapting large models using modern methods (LoRA, QLoRA, SFT, DPO, distillation)
• Architecture and operation of scalable inference systems, balancing latency, cost, and reliability
• Design and maintenance of data systems for high-quality synthetic and real-world training data
• Evaluation pipelines covering model performance, robustness, safety, and bias
• Production deployment - GPU optimization, memory efficiency, latency reduction, and scaling strategy
• Close collaboration with product and application engineering teams (backend, mobile, desktop) to ship AI features that work reliably for real users
• Fast, pragmatic decision-making - shipping improvements quickly and learning from real usage data

What Success Looks Like

• Research and models translate reliably into production-ready systems with clear performance targets
• ML pipelines and inference systems remain stable, efficient, and maintainable at scale
• Production issues are identified and resolved quickly, minimizing user impact
• Continuous, measurable improvement in model performance and user experience over time

Tech Environment

• Python
• PyTorch / JAX
• GPU-based training and inference infrastructure

What We're Looking For

• You've built and shipped real ML systems used by real people - not just research projects or prototypes
• You understand large models deeply, including how and why they fail in production
• You write clean, production-grade code and care about system correctness under real-world constraints
• You're self-directed, pragmatic, and comfortable owning outcomes end-to-end
• You communicate clearly and thrive in small, high-trust, fast-moving teams

Why This Role

This is a high-ownership, high-impact opportunity to shape the core intelligence layer of an AI product built for a truly massive user base - with the autonomy of a startup and the technical depth of a serious ML engineering challenge.