Senior Machine Learning Engineer

• This is a hands-on, high-impact role focused on depth.
• 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
• PyTorch / JAX
• GPU-based training and inference systems
• 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.
• 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.

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