Machine Learning Systems Engineer — Ship Production Models

European Recruitment BV; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

European Recruitment BV is seeking a Member of Technical Staff, Machine Learning to build core ML components and deploy production-grade models. You will work on real systems from day one, focusing on accuracy, latency, and reliability while shipping iterative improvements.

The role emphasizes learning from real-world data, collaborating with senior engineers and product teams, and navigating production constraints to deliver robust ML-powered features.

Qualifications

• Strong foundations in machine learning and modern neural architectures.
• Hands-on experience training, fine-tuning, or deploying ML models.
• Comfortable writing production-quality code and learning new tools quickly.
• Curious, coachable, and eager to learn from real systems in production.
• Able to work through ambiguity with guidance and grow ownership over time.
• Bias toward shipping, iteration, and continuous improvement.

Responsibilities

• Build and improve ML components across data, training, evaluation, and inference.
• Fine-tune and adapt models as part of larger production systems.
• Implement evaluation and testing to understand model behavior.
• Help build and maintain data pipelines for real-world and synthetic data.
• Debug model issues, performance problems, and production incidents.
• Ship improvements iteratively and learn from real user feedback.
• Work closely with senior ML engineers and product teams.
• Work under real production constraints: latency, cost, reliability and safety.

Skills

ML fundamentals

Hands-on ML

Production code

Curious/coachable

Ambiguity handling

Tools

Python

PyTorch

JAX

GPU platforms

Job description

European Recruitment BV is seeking a Member of Technical Staff, Machine Learning to build core ML components and deploy production-grade models. You will work on real systems from day one, focusing on accuracy, latency, and reliability while shipping iterative improvements.

The role emphasizes learning from real-world data, collaborating with senior engineers and product teams, and navigating production constraints to deliver robust ML-powered features.