Principal Machine Learning Engineer

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

You will be responsible for turning research direction into working, production-grade ML systems. This role owns the execution layer of A1’s intelligence – training pipelines, inference systems, evaluation tooling, and deployment.

 

FOCUS

- Build and own end-to-end ML pipelines spanning data, training, evaluation, inference, 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.

- Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.

- Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products.

- Make pragmatic trade-offs and ship improvements quickly, learning from real usage.

- Work under real production constraints: latency, cost, reliability, and safety

 

REQUIREMENTS

- Strong background in deep learning and transformer-based architectures.

- Hands-on experience training, fine-tuning,...