Quantitative Developer

Tower Research Capital•New York City, NY

15d•$150,000 - $200,000•Hybrid

About The Position

Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities. Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization. Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance. At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential. Tower Research Capital seeks a Quantitative Developer to join the Core Engineering team to help build out our Quantitative Execution Services. You will be closely working with researchers and traders on the Central Execution Desk, directly contributing to scale up Tower's Mid-Frequency Trading capabilities. This role sits at the intersection of research and engineering—ideal for someone who has prior experience with execution algorithms and quantitative trading systems, and can translate research ideas into robust, high‑performance production software.

Requirements

Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related STEM field.
2–5 years of professional software‑engineering experience, including production systems written in Python or Rust.
Proficiency in a systems language—Rust preferred (C++/Go also acceptable)—and a desire to deepen that expertise.
Strong CS fundamentals: algorithms, data structures, concurrency, networking, and performance profiling.
Experience with real‑time and/or historical market data, or other high volume time series data.
Familiarity with SQL and at least one columnar/time‑series store (e.g., kdb+, ClickHouse, InfluxDB, Parquet/Arrow).
Proficiency with Linux development, Git, containers, and CI/CD workflows.
Excellent problem‑solving abilities, attention to detail, and clear communication skills

Nice To Haves

Hands‑on exposure to execution algos, TCA, order routing, or market‑impact modeling.
Understanding of broker and exchange order entry APIs, and FIX/native protocols.
Experience building distributed systems with message buses (Kafka, ZeroMQ) and asynchronous I/O (e.g. tokio)
Knowledge of statistical/ML libraries and tooling (NumPy, pandas, scikit‑learn, PyTorch); experience shipping inference in production.
Experience with cloud or on‑prem orchestration and scheduling (Kubernetes, Ray, HTCondor, SLURM).

Responsibilities

Design, implement, and maintain high performance services in Rust and Python for our execution desk, including algo wheel, smart order routers, internalisers, etc.
Partner closely with our quantitative researchers to take research prototypes to production: refactoring, adding tests, telemetry, SLIs/SLOs, and CI/CD automation.
Write robust pipelines for market‑data ingestion, model training/inference, and post‑trade analytics.
Optimize for reliability and performance (throughput, tail‑latency, memory footprint) on distributed systems running in production trading environments.
Establish best practices in code quality, observability, and on‑call readiness; write clear documentation to enable effective collaboration across research and engineering.

Benefits

Generous paid time off policies
Savings plans and other financial wellness tools available in each region
Hybrid working opportunities
Free breakfast, lunch and snacks daily
In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more)
Company-sponsored sports teams and fitness events (JPM Corporate Challenge, Cycle for Survival, Wall Street Rides FAR and more)
Volunteer opportunities and charitable giving
Social events, happy hours, treats and celebrations throughout the year
Workshops and continuous learning opportunities

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