Member of Technical Staff, Machine Learning

ABOUT A1 There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native. Our mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows, with minimal prompting. Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. Our objective is to help users complete tasks daily enjoyable with over ~90%* reduced time. ROLE As a Member of Technical Staff, Machine Learning, you will build core ML components. You will work on real production systems from day one, learning how large-scale ML behaves outside of research settings. This role is for engineers who want to develop strong systems judgment by shipping, debugging, and iterating on real-world ML. FOCUS - Build and improve ML components across data, training, evaluation, and inference. - Fine-tune and adapt models as part of larger production systems. - Implement evaluation and testing to understand model behavior. - Help build and maintain data pipelines for real-world and synthetic data. - Debug model issues, performance problems, and production incidents. - Ship improvements iteratively and learn from real user feedback. - Work closely with senior ML engineers and product teams. - Work under real production constraints: latency, cost, reliability, and safety TECH STACK - Python - PyTorch / JAX - Production ML systems running on GPUs IDEAL EXPERIENCE - Strong foundations in machine learning and modern neural architectures. - Some hands-on experience training, fine-tuning, or deploying ML models. - Comfortable writing production-quality code and learning new tools quickly. - Curious, coachable, and eager to learn from real systems in production. - Able to work through ambiguity with guidanc