Machine Learning Engineer

About the Position

We are seeking a Machine Learning Engineer to join A1, a high-talent team building AI-native productivity applications. This role focuses on building and shipping ML systems used by real users.

Locations

Europe; Hong Kong; Indonesia; Latin America; Malaysia

Employment Type

Full time

Work Location Type

Remote

Department

Machine Learning

Responsibilities

• Build core ML systems powering a proactive, long-horizon AI product.
• Own the full lifecycle: data preparation, training, evaluation, inference, iteration.
• Turn research ideas into production systems that run reliably.
• Debug model failures and system issues using real production signals.
• Ship quickly, measure outcomes, refine, and repeat.
• Collaborate closely with research, product, and engineering teams.
• Mentor and review work from other ML engineers.
• Work under real production constraints: latency, cost, reliability, safety.

Tech Stack

• Python
• PyTorch / JAX
• GPU-based training and inference systems

Ideal Background

• Experience building and shipping ML systems used by real users.
• Strong understanding of how modern ML models behave - and misbehave - in production.
• Ability to write production-quality code and think in systems, not scripts.
• Independent ownership: driving work across the finish line.
• Fast learner, clear communicator, iterative mindset.

Expected Outcomes

• ML models and systems consistently meet accuracy, latency, reliability, and efficiency targets.
• Complex production issues are monitored, debugged, and resolved with minimal disruption.
• Training, inference, and data pipelines are robust, scalable, and maintainable.
• Measurable improvements in ML systems based on real-world signals and user feedback.
• Technical guidance and mentorship that raises the overall ML engineering standard.
• Seamless integration of ML features into products that meet business goals.

About A1

Our client A1 is a small, world-class team with high talent density. They move quickly, make decisions collectively, and balance shipping high-quality work with rapid learning. Structure, sound judgment, and the ability to execute independently are highly valued.

Interview Process

• 3–4 interviews with technical team members.
• Conducted virtually and/or onsite.
• Transparent and efficient decision process.
• Successful candidates will receive an offer to join a team building AI that delivers practical benefits to billions of users globally.