Senior Machine Learning Engineer

Posted Yesterday
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Hiring Remotely in Israel
Remote
Senior level
Artificial Intelligence • Fintech • Software • Financial Services
The Role
The Senior Machine Learning Engineer will own critical ML subsystems, build and ship ML systems, debug production issues, and mentor other engineers. Responsibilities include collaborating cross-functionally, iterating on ML systems based on real-world signals, and ensuring high reliability and efficiency targets are met.
Summary Generated by Built In
Company

A1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows.

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.

 
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.

 
Focus
  • 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

 
Tech Stack
  • Python

  • PyTorch / JAX

  • GPU-based training and inference systems

 
Ideal Experience
  • 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.

 
Outcomes
  • ML models and systems in production 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 over time.

  • Drives measurable improvements in ML systems based on real-world signals and user feedback.

  • Provides mentorship and technical guidance to peers, raising the overall ML engineering standard.

  • Collaborates cross-functionally to ensure ML features integrate seamlessly into products and meet business goals.

 
How We Work

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. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product

 
Interview process

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.

Skills Required

  • Experience building and shipping ML systems used by real users
  • Strong production-quality coding skills working with ML models
  • Ability to debug model failures and system issues in production
  • Experience with data preparation, training, evaluation, and inference
  • Willingness to mentor and review work from other ML engineers
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The Company
Selangor, Selangor
253 Employees
Year Founded: 2019

What We Do

Our mission is to develop technology based solutions to improve financial inclusion. We develop new & innovative platforms & services globally. For example, we are the first platform to simplify and digitise comprehensive life and medical insurance, supported by AI agent. BJAK is the largest insurance platform in Southeast Asia. If you enjoy building cutting edge platform-ecosystems that gives equal access to financial services to everyone at scale, join us

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