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AI & Trading Engineer

Galaxydigitalservices

New York, NY (New York) Remote permanent

Posted: February 27, 2026

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Quick Summary

We are seeking a highly skilled AI & Trading Engineer to join our team in New York, NY, to design and implement cutting-edge AI and trading solutions for our institutional digital assets platform.

Job Description

Who We Are:
Galaxy is a global leader in digital assets and data center infrastructure, delivering solutions that accelerate progress in finance and artificial intelligence. We believe that blockchain and digital asset innovation will transform how value moves through the world – and we’re building the products and services to make that future a reality.

Our institutional digital assets platform spans trading, investment banking, asset management, staking, self-custody, and tokenization technology. We also invest in and operate cutting-edge data center infrastructure to power AI and high-performance computing, addressing the growing demand for scalable energy and compute in the U.S.

We work at the intersection of finance and technology, helping institutions, startups, and developers navigate a digitally native economy. Led by CEO and Founder Michael Novogratz, our team blends deep crypto expertise with institutional experience and a shared commitment to shaping the future of Web3 and AI.

Galaxy is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia.

To learn more about our businesses and products, visit www.galaxy.com.

What We Value:

We are a diverse team of free thinkers, and fast movers united to help investors and creators energize the global economy. We are looking for individuals who thrive in a culture of builders and overachievers and embrace high performance, transparent feedback, and a mission-first approach. Our culture shapes our way of working and gets us where we want to be.

• Seek Excellence.

• Be Selective To Be Effective.

• Be Highly Aligned, Loosely Coupled.

• Disagree Transparently.

• Encourage Independent Decision-Making.

• Build Dream Teams.

About the role

We are building an advanced, AI-driven trading platform and are looking for a senior engineer who thrives at the intersection of machine learning, quantitative finance, and production systems. This role is ideal for someone who has worked on real trading or research platforms and wants to apply cutting-edge AI techniques to complex, high-impact problems in the financial markets.

You will help design and scale systems that power the full lifecycle of systematic trading, from data and modeling to simulation, deployment, and live performance analysis.

What you’ll do

· Build and evolve core components of an AI-enabled systematic trading platform.

· Develop and maintain robust backtesting and simulation infrastructure, accounting for transaction costs, slippage, and market impact.

· Partner closely with quantitative researchers and traders to productionize trading strategies and models.

· Design tools and workflows that significantly improve research speed, reliability, and reproducibility.

· Apply machine learning techniques to financial time-series data, including feature engineering, model training, and evaluation.

· Implement monitoring, post-trade analytics, and performance attribution to support continuous improvement.

· Provide technical leadership through architecture decisions, code reviews, and mentorship.

What we’re looking for

· 8+ years of experience in software engineering, machine learning engineering, or quantitative systems.

· Strong programming skills in Python, plus experience with C++, Rust, or Java.

· Hands-on experience with backtesting frameworks, research platforms, or trading systems used in real-world decision-making.

· Solid understanding of machine learning applied to noisy, non-stationary time-series data.

· Familiarity with systematic trading concepts: signal research, execution, portfolio construction, and risk management.

· Experience building and operating production-grade systems.

Nice to have

· Background as a quant developer or research engineer in a systematic trading environment.

· Knowledge of market microstructure, order types, and transaction cost modeling.

· Experience with distributed systems, GPUs, or large-scale ML pipelines.

· Advanced degree in CS, Math, Statistics, Physics, or a related field.

Why join

· Work on core, high-impact systems at the heart of a trading platform.

· High ownership and autonomy in a small, senior technical team.

· Direct influence on both research velocity and live trading outcomes.

· Competitive compensation and long-term growth opportunities.

The base salary ranges included below will be commensurate with candidate experience, expertise and local market. Final offer amounts are determined by multiple factors, including candidate experience and expertise. At Galaxy, we maintain a total compensation philosophy which consists of a competitive base salary, annual bonus, and equity incentives.

Base Salary Range
$200,000—$250,000 USD

Galaxy respects diversity and seeks to provide equal employment opportunities to all employees and job applicants for employment without regard to actual or perceived age, race, color, creed, religion, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression (including transgender status), sexual orientation, marital or partnership or caregiver status, ancestry, national origin, citizenship status, disability, military or veteran status, protected medical condition as defined by applicable state or local law, genetic information or predisposing genetic characteristic, or other characteristic protected by applicable federal, state, or local laws and ordinances.

We will endeavor to make a reasonable accommodation to the known limitations of a qualified applicant with a disability unless the accommodation would impose an undue hardship on the operation of our business. If you believe you require such assistance to complete the application process or to participate in an interview, please contact [email protected].

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