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Quantitative Technologist

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Quantitative Technologist

K4

Quantitative Technologist

Skills

RustGolang

9 months ago

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Important information


Contract type:

Permanent

Location:

New York, NY, USA

Work mode:

Hybrid

Published on:

22 September 2026

What they need


Firm Overview

K4 is a proprietary trading firm and technology provider operating at the intersection of quantitative finance and frontier markets. While many firms compete in established venues, K4 leverages deep domain expertise to systematize liquidity in complex, emerging, and idiosyncratic markets.

At K4, research outcomes drive more than just risk-adjusted returns. We design and deploy the financial infrastructure that powers modern markets, partnering with leading research organizations to solve engineering problems at a global scale. We distinguish ourselves by building the "rails" for the world's most complex markets—creating a technological edge that is difficult to replicate.

The Role

As a Quantitative Technologist, you will have holistic ownership over the firm’s technical ecosystem. You will operate beyond the scope of a traditional developer, acting as an architect for mission-critical platforms that drive both our automated trading business and our commercial product suite.

This role requires a mindset shift from "task execution" to "solution engineering." You will leverage the firm’s deep market expertise to identify structural gaps in frontier market access—whether it be fragmented data, unreliable connectivity, or unique matching engine behaviors—and build sophisticated, reusable systems to solve them.

Key Responsibilities

  • Product Engineering & Infrastructure: Designing and maintaining the foundation upon which our business runs.
  • Commercial Trading Solutions: Architecting the backbone for K4’s external-facing product suite (e.g., trading terminals platforms, and data products).
  • Market Access Platforms: Building normalized gateways that abstract away the complexities of diverse, high-friction exchange protocols.
  • Research Ecosystems: Building distributed simulation environments and data lakes that allow researchers to backtest strategies against petabytes of noisy, real-world data with deterministic accuracy.
  • Reliability Engineering: Designing fault-tolerant systems that maintain high availability even in unstable network environments.
  • Systematic Trading Implementation: Translating quantitative insights into high-performance production code.
  • Strategy Evolution: Collaborating with researchers to implement and optimize fully automated trading strategies.
  • Performance Optimization: Tuning the full stack—from network drivers to application logic—to minimize latency and jitter in execution.

Technical Competencies

  • Systems Programming: Proficiency in low-level languages (e.g., Rust, C++, or Go) with a strong grasp of memory management, concurrency models, and processor architecture.
  • Distributed Systems: Experience designing scalable systems that handle high throughput and inter-process communication (TCP/UDP/Multicast).
  • Data Structures & Algorithms: A rigorous understanding of algorithmic complexity and the ability to apply it to real-time constraints.

We are looking for polyglot systems engineers who prioritize the right tool for the job. We prioritize architectural intuition and first-principles thinking over specific language trivia. We want engineers who understand the hardware-software interface and can adapt to new paradigms quickly.

To apply, please submit your Resume/CV. We are also interested in seeing examples of complex systems you have built or open-source contributions that demonstrate your engineering philosophy.

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