Applied ML Research Engineer - Benchmark & Scale ML Stack

Tradermath; New York (NY); Hybrid; USD 200,000 - 300,000; Full time

Benefits offered by this job

Generous paid time off

Hybrid working opportunities

Free breakfast, lunch, snacks

Job summary

Tower Research Capital in New York is seeking an AI/ML Applied Research Engineer to join the cutting-edge intersection of our central ML infrastructure and research teams. The role focuses on acting as Customer Zero for our internal ML Research platform and expanding it to benchmark, rapidly prototype, and stress-test both software and hardware layers across our distributed ML stack.

You will leverage AI agents and auto-research capabilities to push systems to their limits, identify bottlenecks,

Qualifications

• Proven Python software development experience.
• Hands-on ML model training, evaluation and deployment.
• Experience scaling ML workloads across GPUs and clusters.
• Familiarity with AI agent workflows and LLM tooling.

Responsibilities

• Validate the ML stack end-to-end across training and inference.
• Build abstractions to simplify rapid prototyping of ML models.
• Leverage AI agents to automate experiments and stress-test clusters.
• Share insights and publish findings to guide engineering decisions.

Skills

Python

ML concepts

Distributed compute

AI agent workflows

System profiling

Tools

PyTorch

TensorFlow

Ray

Dask

PyTorch Distributed

LLM tooling

Agentic frameworks

Job description

Tower Research Capital in New York is seeking an AI/ML Applied Research Engineer to join the cutting-edge intersection of our central ML infrastructure and research teams. The role focuses on acting as Customer Zero for our internal ML Research platform and expanding it to benchmark, rapidly prototype, and stress-test both software and hardware layers across our distributed ML stack.

You will leverage AI agents and auto-research capabilities to push systems to their limits, identify bottlenecks,