Machine Learning Engineer Jobs in Arlington Heights, IL

QF Analytics LLC is a fintech company that develops and supports one of the world’s fastest-growing online trading platforms with a monthly trading volume in excess of $11 billion dollars. We are expanding our team aggressively and looking ideally for individuals with trading domain knowledge, who can help develop and support a robust financial trading infrastructure.

The Machine Learning Researcher should be interested in Financial Markets, and will be directly involved in advancing the company’s Data Analysis and Machine Learning capabilities. They’ll be working on cutting edge Quantitative Data Analysis and Machine Learning challenges. Our environment is fast paced and constantly changing; the right candidate must be able to demonstrate strong communication skills, creative solutions, and results-driven behavior in time-sensitive situations.

This opportunity presents an exciting chance for individuals seeking a dynamic work environment. The successful candidate will have the option to work in a hybrid capacity, commuting to offices in Miami, Chicago, Atlanta, Toronto (Canada) or Nassau (Bahamas), fostering a collaborative and engaging atmosphere. Join our team and experience the synergy that comes from working together in person, while also enjoying the flexibility and convenience of working from home a couple days a week.

Apply strong data modelling and statistical skills to develop and implement data-driven solutions.

Curate and prepare data for supervised and unsupervised machine learning projects, ensuring data quality and compatibility.

Manipulate and analyze large datasets, including numerical and categorical data, using appropriate techniques and tools.

Utilize knowledge of classical machine learning and deep learning algorithms to address specific problem domains.

Apply ML/AI tools like TensorFlow/PyTorch to build and train models for various applications.

Interface with databases to gather relevant information for analysis and modeling.

Fuse and correlate different data feeds to gain insights and enhance predictive capabilities.

Stay updated with the latest advancements in the field of machine learning and artificial intelligence, including tools, conferences, and industry blogs.

Possess a solid understanding of capital markets concepts and quantitative financial methods to effectively apply machine learning techniques in finance-related projects.

Master’s Degree in Mathematics, Engineering, Physics or related field;

Proficiency in Python;

Strong understanding of SQL for data manipulation and extraction;

Solid knowledge of probability and statistics to effectively analyze and interpret data;

Knowledge of applied mathematics, including convex optimization, quadratic programming, and partial differential equations;

Proficiency in analyzing and interpreting data, along with the ability to question it and draw meaningful conclusions;

Hands‑on approach and flexibility to apply various methods and techniques to generate actionable ideas;

Proactive, self‑motivated, and team‑oriented mindset, demonstrating strong analytical thinking;

Strong conceptualization, innovation, and problem‑solving skills;

Ability to communicate effectively through verbal and written presentations;

PhD in Mathematics, Engineering, Physics or related field;

4-8 years experience working in Machine Learning;

Experience with deep learning frameworks like TensorFlow or PyTorch;

Familiarity with C# and .NET framework;

Familiarity with Azure Environments; specifically Azure Data Functions;

Familiarity with Docker initialization and environment management.

Flexible work arrangements when in office (including working from home periodically);

Competitive salaries, often better than industry, for comparable roles;

Daily premium lunch catering, and keeping the office stacked with fruits and snacks;

Arcade, foosball, snooker, pingpong, and fully equipped game room with latest generation gaming consoles on site;

Comprehensive health benefits plan that kicks in after 90 days of successful employment, including access to exclusive employee discounts;

Bonus and incentive programs.