Quantitative Developer (Machine Learning)

Location: New York office, onsite 5 days per week

Annual base salary: $175,000–$250,000, plus an annual discretionary bonus.

Company

hirify.global is a diversified trading firm operating technology-driven strategies across global financial markets and non-traditional areas including real estate, venture capital, and cryptoassets.

What you will do

• Design and build the research and trading platform, including data pipelines, backtesting and simulation frameworks, portfolio and execution tooling, and research APIs.
• Work with quantitative researchers to implement studies, test hypotheses, and convert research ideas into production systems.
• Develop and productionize statistical and machine learning models across feature generation, training, backtesting, deployment, and live monitoring.
• Build reliable infrastructure for large historical and real-time datasets with strong point-in-time correctness, reproducibility, performance, and usability.
• Improve the performance and scalability of computationally intensive research and production workloads.
• Define architecture, testing standards, development practices, and operational processes while taking systems and strategies from prototype to live production.

Requirements

• Bachelor’s, master’s, or PhD degree in computer science, computer engineering, or another technical field.
• At least two years of production software development experience, primarily with Python and/or C++.
• Strong fundamentals in software design, debugging, testing, performance analysis, operating systems, concurrency, networking, and system performance.
• Fluency in a UNIX/Linux environment and experience delivering production systems in fast-moving or ambiguous environments.
• High ownership, sound judgment, practical problem-solving ability, and clear cross-disciplinary communication.
• Ability to work from the New York office 5 days per week.

Nice to have

• Experience developing deep learning systems with PyTorch.
• GPU computing, kernel development, distributed training, or performance optimization experience.
• Experience operating machine learning or data pipelines in production.
• Experience with large-scale, concurrent, high-throughput, or performance-sensitive systems.
• Strong foundations in mathematics, statistics, optimization, or machine learning.

Culture & Benefits

• Early-stage opportunity to shape a systematic trading business within an established firm.
• Technical autonomy with mentorship from quantitative researchers and trading-system engineers.
• End-to-end ownership spanning software, data, machine learning, deployment, and live trading.
• AI-assisted coding, testing, and research embedded in the development workflow.
• Medical, pharmacy, dental, and vision insurance; 401(k) with discretionary employer match; disability and life insurance; HSA; and FSA.