Hiring a Java Analyst Developer

By
If you have enjoyed this blog and looked at the OpenHFT projects such as Java Chronicle you might be interested in applying for this role.  You would learn a lot working on technically challenging projects.


Higher Frequency Trading is a consulting and software developer company offering training, performance consulting, system development and open source software to clients in the USA and Europe. We are looking to expand the development and support for existing and new open source projects.
This is a great opportunity to get into High Frequency Trading as you will be developing and supporting open source software which is used in HFT systems for investment banks, hedge funds and trading houses.  The project area is https://github.com/openhft
Requirements
- 5 to 10+ years commercial programming, preferably with some support experience
- you must be passionate about low level coding in Java
- you must have worked on open source projects  (Please provide such examples)
- you will be interested into breaking into high frequency trading
Skills you will have or acquire in Java.
- low level, low latency software
- GC-less coding
- lock-less multithreading
- off heap, thread safe, shared memory manipulation
The position could be part time or full time, contract or permanent.  Full time roles would offer more training.


Visas will not be considered, but working from home in any country may be considered.

Please contact bee.gill@higherfrequencytrading.com with your CV, a list of open source projects you have worked on and your salary expectations.

Comments

  1. Mohan Radhakrishnan6 February 2014 at 14:34

    Do you have one or many part-time positions ?

    ReplyDelete
  2. Peter Lawrey6 February 2014 at 20:52

    @mohan I have seven part time developers which is enough for now. If you send you CV, you can be considered if a position opens in the future.

    ReplyDelete

Post a Comment

Popular posts from this blog

Java is Very Fast, If You Don’t Create Many Objects

By
Image
  You still have to watch how many objects you create. This article looks at a benchmark passing events over TCP/IP at 4 billion events per minute using the net.openhft.chronicle.wire.channel package in Chronicle Wire and why we still avoid object allocations..  One of the key optimisations is creating almost no garbage. Allocation is a very cheap operation and collection of very short-lived objects is also very cheap. Does this really make a difference? What difference does one small object per event (44 bytes) make to the performance in a throughput test where GC pauses are amortised? While allocation is as efficient as possible, it doesn’t avoid the memory pressure on the L1/L2 caches of your CPUs and when many cores are busy, they are contending for memory in the shared L3 cache.  Results Benchmark on a Ryzen 5950X with Ubuntu 22.10. JVM Vendor, Version No objects Throughput, Average Latency* One object per event Throughput, Average Latency* Azul Zulu 1.8.0_322 60.6 M event/s, 528
Read more

System wide unique nanosecond timestamps

By
A Unique Identifier can be very useful for tracing. Those ids are even more useful when they contain a high-resolution timestamp.  Not only do they record the time of an event, but if unique can help trace events as they pass through the system. Such unique timestamps however can be expensive depending on how they are implemented.   This post explores a lightweight means of producing a unique, monotonically increasing system-wide nano-second resolution timestamp available in our open-source library. Uses for Unique Identifiers Unique identifiers can be useful to associate with a piece of information so that information can be referred to later unambiguously. This could be an event, a request, an order id, or a customer id. They can naturally be used as a primary key in a database or key/value store to retrieve that information later. One of the challenges of generating these identifiers is avoiding creating duplicates while not having an increasing cost.  You could record every identi
Read more

Comparing Approaches to Durability in Low Latency Messaging Queues

By
Image
  A significant feature of Chronicle Queue Enterprise is support for TCP replication across multiple servers to ensure the high availability of application infrastructure. I generally believe that replicating data to a secondary system is faster than syncing to disk, assuming the round trip network delay wasn’t high due to quality networks and co-located redundant servers. This is the first time I have benchmarked it with a realistic example. Little’s Law and Why Latency Matters In many cases, the assumption is that the latency won't be a problem as long as throughput is high enough. However, latency is often a key factor in why the throughput isn’t high enough. Little’s law states, “ the long-term average number  L  of customers in a  stationary  system is equal to the long-term average effective arrival rate  λ  multiplied by the average time  W  that a customer spends in the system”. In computer terminology, the level of concurrency or parallelism a system has to support must be
Read more