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.
 RoleAs Technical Lead, Machine Learning, you own the execution layer of A1’s intelligence.
You translate research direction into reliable, scalable, production-grade ML systems.
This role sits at the intersection of research, infrastructure, and product.
You are responsible for making models trainable, deployable, observable, and performant under real-world constraints.
What You'll DoOwn end-to-end ML system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
Architect and operate scalable inference systems, balancing latency, cost, and reliability.
Design and maintain data systems for high-quality synthetic and real-world training data.
Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.
Make pragmatic trade-offs and ship improvements quickly, learning from real usage.
Work under real production constraints: latency, cost, reliability, and safetyOutcomesResearch and models.