Staff ML Engineer: Production-Ready Models & Systems

DNA325; Madrid; On-site; EUR 90,000 - 130,000; Full time

Job summary

DNA325 is seeking a Member of Technical Staff, Machine Learning, to build core ML components and ship systems from day one. You'll work on production ML, from data pipelines to inference, collaborating with senior ML engineers and product teams.

You'll focus on latency, cost, reliability, and safety, fine-tune models, and help maintain production-grade code. Compensation includes base salary and equity, with remote-first policy and location-based adjustments.

Qualifications

• Strong foundations in machine learning and modern neural architectures.
• Some 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 production systems.
• Able to work through ambiguity with guidance, growing ownership over time.
• A 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 foundations

Neural architectures

Training/fine-tuning

Production code

Ambiguity handling

Shipping mindset

Tools

Python

PyTorch

JAX

Job description

DNA325 is seeking a Member of Technical Staff, Machine Learning, to build core ML components and ship systems from day one. You'll work on production ML, from data pipelines to inference, collaborating with senior ML engineers and product teams.

You'll focus on latency, cost, reliability, and safety, fine-tune models, and help maintain production-grade code. Compensation includes base salary and equity, with remote-first policy and location-based adjustments.