Senior Machine Learning Engineer

Harnham; Amsterdam; On-site; EUR 100,000 - 130,000; Full time

Benefits offered by this job

Competitive salary with performance-related bonuses

Opportunity to work in a highly innovative environment

Flexible working arrangements

Job summary

A global proprietary trading firm in Amsterdam is seeking a Senior Machine Learning Engineer to develop a research framework that drives trading strategies. The role involves leading model training and deployment while collaborating with quantitative researchers. Candidates should have a Master's or PhD and at least 5 years of MLOps experience, with strong Python skills. The position offers a competitive salary and an innovative working culture.

Qualifications

• 5+ years of hands-on experience in MLOps or research engineering.
• Proven experience designing and deploying end-to-end ML pipelines.
• Experience with modern cloud platforms (AWS, GCP, Azure).

Responsibilities

• Lead the development of a research framework for model training and deployment.
• Build tools for testing hypotheses and refining data-driven trading strategies.
• Deploy and train ML models.

Skills

Expert in Python

ML libraries (TensorFlow, PyTorch, scikit-learn)

Experience with RESTful APIs

Hands-on experience in MLOps

Strong understanding of Agile practices

Education

Master’s or PhD in a relevant quantitative or technical field

Tools

Docker

Kubernetes

Big Data frameworks (Spark, Dask, Ray)

Job description

Senior Machine Learning Engineer

Location: Amsterdam, North Holland, Netherlands

Overview

Harnham Amsterdam, North Holland, Netherlands

Up to 130k annually + benefits (bonus)

About the Company

A leading global proprietary trading firm with an entrepreneurial and innovative culture. Known for combining deep technical expertise with fast-paced decision-making, the firm thrives on creativity, collaboration, and delivering cutting-edge data-driven trading strategies.

The Role

As a Senior Research Engineer, you will lead the development of a research framework that drives systematic trading strategies and integrates seamlessly with the firm’s production platform. Your mission is to expand a high-impact platform into a global standard for model training, deployment, and optimization. You’ll work closely with ML researchers and quantitative researchers and traders to turn hypotheses into robust, scalable, and data-driven solutions.

What You Will Do

• Lead the design, development, and global rollout of the research framework for model training, backtesting, and production deployment


• Build tools and frameworks for testing hypotheses and refining data-driven trading strategies


• Deploy and train ML models


• Collaborate with business stakeholders to refine requirements, gather feedback, and iterate on research tools and infrastructure

What You Need to Succeed

• Master’s or PhD in a relevant quantitative or technical field


• 5+ years of hands-on experience in MLOps or research engineering


• Expert in Python and ML libraries such as TensorFlow, PyTorch, and scikit-learn


• Proven experience designing and deploying end-to-end ML pipelines (data preprocessing, model training, deployment, monitoring)


• Experience with RESTful APIs, microservices, and modern cloud platforms (AWS, GCP, Azure)


• Familiarity with Big Data frameworks (Spark, Dask, Ray) and containerization (Docker, Kubernetes)


• Strong understanding of modern software development practices: Agile, version control, automated testing, CI/CD, and observability


• Experience with data visualization, reporting, and querying databases for large-scale data processing

What’s on Offer

• Competitive salary with performance-related bonuses


• Opportunity to work in a highly innovative, entrepreneurial, and global team


• Exposure to cutting-edge technologies and state-of-the-art quantitative research


• Dynamic, collaborative, and intellectually challenging environment


• Offices in London, Amsterdam, Chicago, and New York, with flexible working arrangements

Job Details

• Seniority level: Mid-Senior level


• Employment type: Full-time