Sr & Staff Machine Learning Engineer

European Recruitment BV; United States; On-site; USD 180,000 - 280,000; Full time

Job summary

European Recruitment BV in the United States seeks a Senior & Staff Machine Learning Engineer to own critical ML subsystems in production, designing practical solutions and shipping systems that operate reliably at scale.

This hands-on, high-impact role focuses on depth, end-to-end ownership from data preparation to inference, and collaboration with research, product, and engineering to deliver real user impact.

Qualifications

• You write production-quality code and think in systems, not scripts.
• You own ML subsystems end-to-end and ship reliable systems at scale.
• You learn fast and communicate clearly, improving through iteration.

Responsibilities

• Build core ML systems powering a proactive AI product.
• Own data prep, training, evaluation, inference, and iteration end-to-end.
• Turn research ideas into production-ready systems with real user impact.
• Debug production issues using real signals and monitor performance.

Skills

Independent ownership

Systems thinking

Production-quality code

Fast learner

Tools

Python

PyTorch / JAX

GPU training/inference

Job description

Sr & Staff Machine Learning Engineers

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.