Research Engineer, Pre-Training (AI)

Location: New York, London, or Chicago

Annual base salary: $300,000–$350,000 USD

Company

hirify.global conducts quantitative research and develops technologies for global financial markets, including machine-learning-powered trading systems.

What you will do

• Develop massive-scale foundation models for understanding and predicting financial markets.
• Own the training stack, including fault-tolerant infrastructure across thousands of GPUs and TPUs.
• Build high-throughput data pipelines processing petabytes of market data.
• Design custom kernels and optimize mixed-precision training and model parallelism.
• Co-design new model architectures with quantitative researchers, engineers, and ML experts.
• Improve pre-training performance and reliability for systems that affect live trading.

Requirements

• Track record of measurable performance improvements in large-scale distributed training.
• Published research in efficient training methods, scaling laws, architectures, or ML systems.
• Experience with numerical computing, HPC, or distributed systems, including GPUs/TPUs, NVLink or InfiniBand, Kubernetes or Slurm, and operating-system internals.
• Expertise in Python and modern deep-learning frameworks such as PyTorch or JAX.
• MS or PhD in computer science, machine learning, physics, mathematics, or a related quantitative field, or equivalent frontier-lab experience.
• Strong problem-solving, engineering judgment, communication, and collaboration skills.

Nice to have

• CUDA kernel development, Triton, Pallas, CuTe DSLs, PyTorch/JAX internals, XLA optimization, or FPGA/ASIC acceleration experience.
• Knowledge of reinforcement learning, post-training, or fine-tuning.
• Knowledge of financial markets or trading.

Culture & Benefits

• Research-driven environment focused on innovation, collaboration, and quantitative problem-solving.
• Medical, dental, and vision insurance.
• HSA, FSA, dependent care, life insurance, and AD&D options.
• Paid vacation, holidays, and parental leave.
• Retirement plan with employer match and wellness programs.
• Discretionary bonus eligibility.