Modeling Workflow Specialist (GPU)

Location: New York, United States; hybrid work with flexible in-office days

Base pay: $165,000–$300,000 per year, with potential additional compensation and benefits

Company

hirify.global is a quantitative investment management and trading firm using technology, artificial intelligence, data science, and quantitative research to identify market opportunities.

What you will do

• Analyze CPU-based quantitative modeling workflows and identify high-impact opportunities for GPU acceleration.
• Re-engineer modeling tools and pipelines to use GPU parallelism.
• Work directly with modelers to validate workflow correctness and improve throughput.
• Define GPU infrastructure requirements based on actual workload characteristics.
• Translate modeling-domain requirements into technical specifications and bridge modeling teams with GPU specialists.

Requirements

• BS or MS degree in science, technology, engineering, or mathematics.
• At least 1 year of experience required; 2–10 years preferred.
• Deep experience with quantitative modeling platforms and tooling, including building or maintaining systems used by modelers.
• Understanding of the full modeling lifecycle: feature engineering, simulation, model training, validation, and production deployment.
• Familiarity with the Python scientific computing ecosystem, including NumPy, Pandas, and scikit-learn.
• Strong relationship-building skills and the ability to work directly with modelers.

Nice to have

• Experience profiling and optimizing computational workloads.
• Familiarity with NVIDIA GPU-accelerated scientific computing tools, including CuPy, RAPIDS, and cuDF.
• Background in distributed computing or high-performance computing.

Culture & Benefits

• Fully paid medical and dental insurance premiums for employees and dependents.
• Competitive 401(k) match, employer-paid life and disability insurance, and paid caregiver leave.
• Tuition reimbursement plus conference and training sponsorship.
• Generous vacation and unlimited sick days.
• Onsite gyms with laundry service, wellness activities, casual dress, snacks, and game rooms.
• Flexible in-office days with a budget for home office setup.