Quantitative Software Developer

Point72 is hiring a Quantitative Software Developer in New York, United States. Level rates it ; you can apply on Point72.

Level's read on this job

Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include TensorFlow, scikit-learn and JAX.
Level lists 199 other open roles at Point72.

AI in this role

TensorFlowscikit-learnJAX

ABOUT CUBIST:

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

RESPONSIBILITIES:

Building components for both live trading and simulation
Refining and increasing automation and robustness of the research infrastructure including alpha estimation, risk modeling, and backtesting components
Building tools for signal blending, simulation, portfolio construction, the research framework, and dashboards
Maintaining and updating the platform, ensuring its stability, robustness, and security
Developing robust data checking and storage procedures
Troubleshooting and resolving any systems related issues and handle the release of code fixes and enhancements

REQUIREMENTS:

Bachelor’s degree or higher in computer science or other STEM discipline
Advanced proficiency in Python and its ecosystem (numpy, pandas, polars, scikit-learn), with an understanding of Python and library internals
Experience contributing to core Python numerical libraries is a huge plus (numpy, tensorflow, torch, jax)
Proficiency with Linux
Hands-on experience with software architecture and engineering best practices (testing, CI/CD, monitoring, profiling, version control)
Strong quantitative and analytical skills; command of linear algebra, statistics, and machine learning would be helpful
Proficiency with C/C++ is a plus
Experience with designing and implementing trading systems is a plus
Commitment to the highest ethical standards

How we rate this

Quantitative Software Developer at Point72 rates 83 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Quantitative Software Developer is an open job at Point72.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in New York.
The job was posted on June 10, 2025.
Applications are handled by Point72. Apply on Point72

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

TensorFlowscikit-learnJAX

Also common in software engineer jobs at this level

LLM AWS AI agents Kubernetes Generative AI Java

Pay

Typical software engineer job: $167k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

What's a project where you used TensorFlow hands-on?
Walk me through how you've used scikit-learn in your day-to-day work.
What are the limits of JAX that you've run into, and how did you work around them?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: TensorFlow, scikit-learn, and JAX. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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