Machine Learning Research (Intern)
At a glance
Junior Machine Learning Engineering role at Pinely. Amsterdam · contract.
Pay not stated Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Help research and build high-frequency trading strategies using machine learning, deep learning and reinforcement learning
- Study trading patterns and market microstructure to spot potential opportunities
- Work with developers and researchers to put strategies into practice and improve how they perform
- Support quantitative strategy design and help refine existing approaches
What you bring
- You have a strong grounding in probability and mathematical statistics
- You have practical machine learning experience and can program confidently in Python
- You are keen to pursue research
Who this fits
This internship suits someone starting out in machine learning research who wants hands-on work with financial data and trading strategies. The role is based onsite in Amsterdam, runs for three to six months, and is offered on a contractor basis.
From the employer
We are excited to offer an internship opportunity for a Machine Learning Research (Intern) to join our Amsterdam-based team. As part of our research group, you will contribute to innovative projects focused on developing and improving HFT strategies using ML, DL and RL techniques. You will work closely with experienced researchers and engineers, gaining hands-on experience in applying cutting-edge ML methods to real-world financial data. This internship offers a unique opportunity to explore the intersection of AI and quantitative finance, contributing to our ongoing efforts to automate and optimize trading strategies in a highly dynamic environment.
The internship duration can range from 3 to 6 months, depending on the team and the intern’s availability. Upon successful completion, you may be offered a full-time position at Pinely.
Responsibilities
- Participate in conducting groundbreaking research and development of high-frequency trading (HFT) strategies;
- Analyzing high-frequency trading strategies and market microstructure to identify new trading opportunities;
- Collaborating with developers and other researchers to implement and optimize trading strategies;
- Contributing to the improvement of existing trading strategies and assisting researchers in quantitative strategy design.
Requirements
- Passion for research;
- Deep knowledge of probability theory and mathematical statistics;
- Experience in machine learning;
- Proficiency in Python.
Would be great if you had this
- Participation in ML competitions, hackathons, or mathematical / programming Olympiads;
- Experience with big data processing technologies (MapReduce, Hadoop, Apache Spark);
- Demonstrated performance in competitive programming contests;
- Engagement with ML conferences.
What we offer
- The team which consists of great minds, including Kaggle Grandmasters, ACM ICPC World Finalists and published research findings in A* conferences;
- The versatile and reliable infrastructure to support your strategies and innovations and the capability to test ideas daily on a real-time production leaderboard, fostering a dynamic environment for experimentation and refinement;
- A modern and well-equipped office designed for productivity and comfort;
- Friendly work environment, we value and prioritize a healthy work-life balance to support overall well-being of the team;
- Corporate and team`s events.