Staff Machine Learning Engineer

A1 is building a proactive AI system that understands context across conversations, plans actions, and carries work forward over time.

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.

• 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

• Python

• PyTorch / JAX

• GPU-based training and inference system

• You have built or shipped real ML systems used by people, not just demos.

• You are comfortable working with large models and understanding their failure modes.

• You write strong, production-grade code and care about system correctness.

• You are self-directed, pragmatic, and take full ownership of outcomes.

• You communicate clearly and collaborate well in small, high-trust teams.

Our organization is very flat and our team is small, highly motivated, and focused on engineering and product excellence. All members are expected to be hands-on and to contribute directly to the company’s mission.

If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.

Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.

We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.