[Hiring] Machine Learning Engineer @OnHires

Role Description

As a Machine Learning Engineer , you will own critical ML subsystems in production. This is a hands-on, high-impact role focused on depth and reliability at scale.

• 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.

Qualifications

• 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.

Requirements

• 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.

Benefits

• 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.