Faculty Fellow (Machine Learning)

Location: Bala Cynwyd (Philadelphia Area), Pennsylvania, United States; onsite

Company

hirify.global is a quantitative trading firm using machine learning, advanced quantitative research, and large-scale datasets to develop systematic trading strategies.

What you will do

• Conduct applied machine learning research using large-scale, real-world financial datasets.
• Develop modeling techniques and adapt state-of-the-art algorithms to challenges in quantitative finance.
• Collaborate with researchers and engineers to translate theoretical insights into production-scale systems.
• Contribute to robust, high-performance ML infrastructure.
• Explore research directions aligned with individual interests and evaluate ideas in an industrial setting.
• Foster collaboration across the machine learning and academic research communities.

Requirements

• Faculty members, newly minted PhDs, or postdocs with expertise in machine learning, deep learning, LLMs, statistics, computer science, physics, applied mathematics, or related fields.
• Faculty applicants should be tenured or tenure-track.
• Strong theoretical foundation in machine learning and interest in practical, open-ended problems.
• Strong programming skills, preferably Python.
• Experience with ML frameworks such as PyTorch, TensorFlow, or Jax.
• Intellectual curiosity, adaptability, and a collaborative mindset.

Culture & Benefits

• 12–18 month fully funded faculty fellowship.
• Flexible start date and flexibility in research scope and duration.
• Collaboration with researchers, engineers, and traders in a systematic trading environment.
• Opportunity to develop an applied research portfolio and collaborate on technical research papers.
• Research outputs are subject to proprietary work restrictions.