Senior ML Infra Engineer: Research to Production

Pinely; Amsterdam; On-site; EUR 110,000 - 140,000; Full time

Benefits offered by this job

High base salary

Generous bonus structure

Tuition reimbursement

Job summary

Pinely in Amsterdam is seeking a Senior Research Engineer to build and improve the ML infrastructure powering our deep learning research and trading. You will own the boundary between research and production, turning prototypes into scalable systems and eliminating bottlenecks in the research loop across markets and asset classes.

You will work with researchers and infrastructure teams on training frameworks, datasets, pipelines, distributed training, and observability, with opportunities to

Qualifications

• Strong background in large-scale ML training systems and distributed training.
• ML/data infrastructure, including datasets, storage formats, orchestration, experiment tracking, and configuration.
• Research engineering around large-scale deep learning systems.

Responsibilities

• Turn successful research prototypes into robust implementations that can be trained, validated, and deployed across multiple markets and asset classes;
• Work directly with researchers to remove infrastructure bottlenecks from the research loop - make new ideas easier to prototype, experiments faster to run, and failures easier to understand;
• Build and improve our internal ML platform - training framework, datasets and data pipelines, orchestration, experiment tracking and reproducibility tooling, GPU/compute infrastructure, and tooling for releasing models into production;
• When useful, contribute directly to research: run experiments, investigate model behavior, prototype architectural or optimization ideas, and help push model quality forward.

Job description

Pinely in Amsterdam is seeking a Senior Research Engineer to build and improve the ML infrastructure powering our deep learning research and trading. You will own the boundary between research and production, turning prototypes into scalable systems and eliminating bottlenecks in the research loop across markets and asset classes.

You will work with researchers and infrastructure teams on training frameworks, datasets, pipelines, distributed training, and observability, with opportunities to