About the Role

The Senior Software Engineer for the Research Platform will focus on building and evolving a fully managed compute and data platform layer using advanced technologies like Python, Rust, and C++. This role involves architecting distributed training pipelines and collaborating with quantitative researchers to enhance the firm's trading capabilities.

Responsibilities

Expand platform capabilities across service orchestration, job scheduling, cluster management, and big-data processing.
Build and evolve a fully managed compute and data platform layer using Python, Rust, C++, and JAX.
Architect distributed training pipelines and engineer custom systems to handle GPU memory allocation and pipeline parallelization.
Evaluate and integrate cutting-edge AI technologies and custom CUDA kernels into active research workflows.
Partner directly with traders, quantitative researchers, and infrastructure engineers.

Required Skills

Leadership & Execution: Prior experience leading large-scale engineering projects, establishing technical direction, and promoting sound engineering principles.
Distributed Systems Mastery: Deep expertise in building large-scale, fault-tolerant infrastructure capable of orchestrating 100k+ parallel simulations across hybrid cloud or multi-datacenter environments.
Rust Expertise: Advanced proficiency with ownership, the borrow checker, lifetimes, traits, async/Tokio, channels, atomics, and concurrency primitives (Arc, Mutex).
Systems & Data Structure Fundamentals: Solid grip on data structures and low-level mechanics.
Algorithms & Performance Analysis: Strong fluency in Big-O analysis and memory footprint optimization.
Python Engineering: Deep expertise in Python for API, tooling, and research ecosystem design.
Collaboration: Excellent communication skills to interface directly with quantitative researchers and hardware engineers.

Preferred Qualifications

Experience with C++ systems programming or writing custom CUDA kernels.
Hands-on work with JAX, deep learning frameworks, or distributed model training at scale.
Direct background optimizing GPU memory layouts and pipeline parallelization.

Compensation and Benefits

Highly competitive base salary and bonus structure.

Requirements

Leadership & Execution

Prior experience leading large-scale engineering projects and promoting sound engineering principles.

Distributed Systems Mastery

Deep expertise in building large-scale, fault-tolerant infrastructure.

Rust Expertise

Advanced proficiency with Rust and its concurrency primitives.

Python Engineering

Deep expertise in Python for API and tooling design.

Nice to Have

C++ Systems Programming

Experience with C++ systems programming or writing custom CUDA kernels.

Deep Learning Frameworks

Hands-on work with JAX or distributed model training at scale.

Benefits

Competitive Salary

Highly competitive base salary and bonus structure.