Senior Machine Learning Engineer

Role

Full-time

Senior

Software Development

Logistics

Remote

Requirements

EU/EFTA permit

Description

Role As a Senior Member of Technical Staff, Machine Learning, you are an independent owner of critical ML subsystems in production. You take ambiguous problems, design practical solutions, and ship systems that operate reliably at scale. This is a hands-on, high-impact role focused on depth.

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.

Requirements

You have built and shipped ML systems used by real users.
You understand how modern ML models behave — and misbehave — in production.
You write strong, production-quality code and think in systems, not scripts.
You take ownership, work independently, and push work across the finish line.
You learn fast, communicate clearly, and improve through iteration.

Tech stack

PythonPyTorchJAXGPU-based training and inference systems

Benefits

The best products today in the world were built by small, world class teams.
We are a high talent density and hands-on team.
We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning.

Company

bjakcareer

Software

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.