Senior Machine Learning Engineer

Stack

Responsibilities

• ▹Build core ML systems that power a proactive, long-horizon AI product
• ▹Own work end-to-end: data preparation, training, evaluation, inference, and iteration
• ▹Turn research ideas into working systems that run reliably in production
• ▹Debug model failures and system issues using real production signals
• ▹Iterate quickly: ship, measure outcomes, refine, and repeat
• ▹Collaborate closely with research, product, and engineering to deliver real user impact
• ▹Mentor and review work from other ML engineers through example and technical judgment
• ▹Work under real production constraints: latency, cost, reliability, and safety

Requirements

• ▹Track record of building and shipping ML systems used by real users
• ▹Understanding of how modern ML models behave — and misbehave — in production
• ▹Strong, production-quality code and systems thinking, not just scripts
• ▹Ownership mentality, independent work, ability to push work to completion
• ▹Fast learner, clear communicator, improves through iteration
• ▹Tech stack: Python, PyTorch/JAX, GPU-based training and inference systems

Soft skills

About the company

A1's mission is to build a proactive smart assistant for everyday users, bringing intelligence to conversations, errands, and workflows with minimal prompting. The product is built around reliable long-running workflows, persistent context, and real-world task completion, aiming to cut users' daily task time by roughly 90%.