Trading ML Systems Engineer - Distributed Training

Fintal Partners; New York (NY); On-site; USD 185,000 - 230,000; Full time

Job summary

Fintal Partners in New York is hiring engineers to build the distributed training and inference systems that take models from research into production. You’ll work side-by-side with researchers and traders on a trading floor-like environment, owning critical, IC-heavy infrastructure projects.

The role focuses on scaling training/inference at scale, optimizing for latency, and expanding a GPU footprint from thousands to tens of thousands, with top-tier compensation for engineers who can execute

Qualifications

• Experience scaling training and inference infrastructure.
• Deep PyTorch fluency and performance-focused mindset.
• Distributed systems with multi-GPU/multi-node training and model serving.
• Hands-on contributor, not a strategy seat.
• Experience at top tech firm, trading firm, or a strong big-tech + startup combo.
• 3+ years of relevant experience.

Responsibilities

• Build and scale distributed training systems for large models.
• Develop low-latency inference pipelines to production.
• Work directly with researchers training the models and the traders/quants relying on them.
• Operate on a rapidly growing GPU footprint (low thousands today, scaling into the tens of thousands).

Skills

PyTorch

Distributed systems

Performance engineering

Hands-on building

Trading background

3+ years experience

Job description

Fintal Partners in New York is hiring engineers to build the distributed training and inference systems that take models from research into production. You’ll work side-by-side with researchers and traders on a trading floor-like environment, owning critical, IC-heavy infrastructure projects.

The role focuses on scaling training/inference at scale, optimizing for latency, and expanding a GPU footprint from thousands to tens of thousands, with top-tier compensation for engineers who can execute