Senior Deep Learning Researcher - Transformers & AI

Internetwork Expert; Amsterdam; On-site; EUR 90,000 - 130,000; Full time

Benefits offered by this job

High base salary

Generous bonus

Cutting-edge hardware

Ownership over initiatives

Access to exchanges

Flexible workflow

Tuition reimbursement

Job summary

Internetwork Expert in Amsterdam is seeking a Senior Deep Learning Researcher to contribute to cutting-edge AI and ML research. The role is suited for an IC who can work independently for at least one year on high-level research advancing the HFT field.

Responsibilities include conducting original research in AI/ML, developing modern deep learning architectures, and analyzing large, noisy datasets to extract meaningful insights.

Qualifications

• Equivalent research experience such as published research findings or a PhD/MD in a quantitative discipline.
• Strong background in ML and mathematical statistics with experience analysing large, unstructured datasets.
• Practical experience with modern DL architectures, especially transformers and their variants.
• Proficient programming skills (Python preferred).
• Hands-on experience in conducting high-quality research.

Responsibilities

• Conduct original research in AI, ML, and related quantitative fields.
• Develop and experiment with modern deep learning architectures.
• Analyse large, unstructured and noisy datasets to extract meaningful insights.
• Continually explore new methodologies and technologies to enhance research outcomes.

Skills

ML & statistics

DL transformers

Python

Research experience

Independent IC

Education

PhD or MD in CS/EE/Math

Job description

Internetwork Expert in Amsterdam is seeking a Senior Deep Learning Researcher to contribute to cutting-edge AI and ML research. The role is suited for an IC who can work independently for at least one year on high-level research advancing the HFT field.

Responsibilities include conducting original research in AI/ML, developing modern deep learning architectures, and analyzing large, noisy datasets to extract meaningful insights.