Latest Interviews

Jane Street on GPUs, Trading, and Hiring: A Conversation with Dwarkesh

Jane Street, Dwarkesh Patel, Ron Minsky, Dan Pontecorvo

Jane Street executes a multi-tiered trading strategy that balances nanosecond-scale FPGA execution with long-horizon AI models while transitioning to a disaggregated global network featuring a $6 billion compute partnership with CoreWeave. The firm prioritizes model architecture diversity and custom hardware, including ARM and NVIDIA infrastructures, to navigate high-noise financial data without relying on single foundation models. This approach is supported by a hiring strategy focused on scarcity-driven talent acquisition and a human-in-the-loop philosophy that maintains critical judgment during complex market anomalies.

System Jitter and Where to Find It: A Whack-a-Mole Experience

Tudor Brindus, Harry

A technical analysis of a simulated low-latency message passing system in OCaml demonstrates that moving from a virtualized environment to bare metal hardware reduces median round-trip latency from 637 nanoseconds to 223 nanoseconds. By sequentially isolating network interrupts with `isolcpus`, disabling timer ticks via `nohz_full`, locking CPU frequencies, and optimizing speculative execution, researchers achieved a final stable median latency of 163 nanoseconds with near-zero jitter. The study concludes that while aggressive overclocking offers marginal speed gains, it introduces unacceptable risks of memory corruption, establishing deterministic bare metal configurations as the necessary standard for reliable high-frequency trading infrastructure.

Charlie Marsh: uv: An Extremely Fast Python Package Manager

Charlie Marsh

Charlie Marsh of Astral introduces UV, a Rust-based Python package manager that functions as a unified drop-in replacement for tools like pip and Poetry by combining installation, dependency resolution, and environment management into a single high-performance workflow. Since its mid-February release, the tool has achieved 16 million monthly downloads by addressing Python's complex dependency graph challenges through advanced SAT solving, Algebraic Decision Diagrams, and a zero-copy architecture that treats virtual environments as ephemeral. UV now commands over 10% of all PyPI requests, leveraging custom version parsing and cache reflinking to enable near-instant package installation and declarative dependency locking.

OCaml Locals Save Allocations | OCaml Unboxed

goldfirere

Jane Street demonstrates how a specialized OCaml compiler reduces memory allocation by introducing the `local` keyword, which restricts value lifetimes to specific function and loop regions. This approach requires replacing standard library functions like `list.iter` with custom implementations that explicitly label arguments as `local` to prevent value escapes, achieving a 50% reduction in word allocations in benchmark tests. Further refinements with the `exclave` keyword and strict type inference drive allocation overhead to near-zero, thereby minimizing garbage collection latency for the experimental feature planned for future upstream integration.

Inferring Locality in OCaml | OCaml Unboxed

The OCaml compiler utilizes an internal allocation discipline that infers local versus global modes for variables and parameters to enable stack-based memory usage and reduce garbage collection overhead. This system prioritizes local inference for arguments while defaulting return values to global to ensure maximum compatibility, with integers serving as a special case that can safely cross mode boundaries under specific annotations. Although this framework enhances performance, current limitations such as standard library functions lacking locality awareness and the need for explicit type signatures to trigger safety checks continue to shape its practical application.

A Jane Street Software Engineering Mock Interview with Grace and Nolen

Grace, Nolen, Nolan, Emily Fortuna, Colton Ogden, Todd Kerpelman, Jen Person, Colt McAnlisley, Dan Galpin, Mark Mirchandani

Nolan and Grace, experienced Jane Street employees, co-created a mock interview simulation featuring a unit conversion challenge that evaluates a candidate's graph-based algorithm design and problem-solving collaboration. During the session, the candidate developed a breadth-first search solution to minimize floating-point errors while iteratively correcting structural flaws regarding bidirectional graph construction and edge cases. The exercise underscores Jane Street's emphasis on code clarity, effective communication, and the ability to refine logic through dialogue rather than demanding immediate optimization or perfect syntax.

A Jane Street Trading Mock Interview with Graham and Andrea

Graham, Andrea, Michael

In a simulated quantitative trading interview, veteran trader Graham guides new hire Andrea through three variations of a die-rolling game designed to test her mathematical modeling and game theory skills. Andrea derives optimal stopping thresholds for static and consumable die scenarios while iterating toward a Nash equilibrium in an adversarial version where the casino actively minimizes her earnings. This exercise highlights Jane Street's evaluation criteria, which prioritize the candidate's ability to clarify rules, articulate a logical thought process, and collaboratively solve complex problems under changing constraints.

Clock Synchronization with Chris Perl

Chris Perl, Ron Minsky

Responding to MIFID 2 regulations, Jane Street engineered a hybrid time synchronization system that combines GPS-driven Precision Time Protocol with Linux-based NTP Interleaved Mode to achieve sub-100-microsecond accuracy across its infrastructure. By leveraging hardware timestamping at the network interface and cross-verifying local and distant time sources, the architecture mitigates standard PTP vulnerabilities while maintaining a simple, inspectable network topology. This design successfully reduces worst-case synchronization errors to approximately 35 microseconds, effectively balancing regulatory compliance with robust fault tolerance.

How to Build an Exchange

Claudio, Ron, Pete

A US equities matching engine utilizes a deterministic, single-instance architecture to process three million messages per second while ensuring fair, latency-critical order execution across thousands of symbols. The system employs C++ and OCaml on a dedicated machine to replace complex distributed consensus with high-speed, single-threaded logic, allowing state machines to recover from failures within 30 to 60 seconds via message log replay. This design guarantees regulatory reproducibility and financial reliability by eliminating consensus overhead, enabling clients to achieve precise atomicity and global risk enforcement through simplified, high-throughput message sequencing.

Why Functional Programming Doesn't Matter

John Hughes, Tony Hoare

Jane Street, a high-frequency proprietary trading firm executing millions of daily trades, attributes its engineering success to OCaml's expressive static types rather than traditional functional features like laziness or strict purity. This type system enforces correctness by eliminating null pointer exceptions, forcing logic updates at compile-time to prevent bugs, and encoding business invariants to exclude impossible states. Consequently, the firm prioritizes predictable performance and verifiable clarity to protect its capital against errors, viewing advanced type systems as a more critical asset than higher-order functions or declarative purity.

Incremental

Sebastian

Sebastian, a developer at Jane Street, presents the Incremental library, a self-adjusting computation system that enables dynamic dependency graphs for high-performance trading, risk modeling, and user interfaces. The discussion details the library's eight-version evolution, which resolved critical memory leak and performance bottlenecks by replacing heap-based sorting with a partial order system and implementing explicit observer tracking. These architectural improvements, combined with GADTs and CPU cache optimizations, allow the system to execute minimal necessary updates while supporting complex dynamic graph topologies.

Effective ML 2011 Harvard CS51 Part 2

Jane Street's engineering philosophy prioritizes explicit error handling, strict boilerplate avoidance, and managed complexity to ensure robust high-frequency trading systems. By leveraging OCaml's predictable performance and enforcing rigorous code review protocols alongside small, autonomous teams, the firm balances mathematical precision with human oversight in a hybrid trading model. This approach treats software development as a discipline of clarity and maintainability, where static typing and disciplined mutation control enable reliable operation in volatile markets.