Campus ML Research Engineer (Full-Time)
AI in this role
Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.
Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.
We are seeking world-class engineers to collaborate with our research, trading, engineering teams to build state-of-the-art ML systems that solve some of the most complex problems in quantitative finance. Whether optimizing training pipelines on high-performance computing clusters, developing low-latency inference systems, or pushing the boundaries of AI research from concept to production, you'll have the opportunity to work on impactful projects in a fast-paced, collaborative environment. If you are driven by technical challenges, eager to work with large-scale systems, and passionate about advancing ML capabilities, we want to meet you.
What you'll do:
- Apply state-of-the-art techniques to complex and challenging domains.
- Work closely with researchers and quants to build flexible and reusable frameworks for financial ML.
- Optimize training pipelines to make the best use of our HPC resources.
- Integrate ML models into production systems where latency matters.
- Work across a mix of programming languages: C / C++ / Python / CUDA and other low-level GPU languages.
- Build large scale ML systems that are observable, performant, and flexible. Help improve productivity by reducing the iteration cycle time on research.
- Other duties as assigned or needed.
Skills you'll need:
This role covers a wide gamut of potential projects and skills. We don't expect everyone to have all of these, but for the applicable areas we are looking for deep technical expertise.
- Creative thinkers who are driven, self-motivated, and eager to solve challenging problems
- Proficiency in Python and/or C++
- Proficiency in Pytorch, JAX, Tensorflow or other DL library.
- Ability to thrive in a collaborative, team-oriented environment
- Expertise in GPU or Accelerator programming (CUDA, Triton, SYCL, ROCm or equivalent)
- Experience building ML systems at large scale (hundreds of TBs of training data, low latency or high throughput inference requirements)
- Excellent written and verbal communication skills in English
- Reliable and predictable availability required
INTERNATIONAL STUDENTS are encouraged to apply. We sponsor work visas for full-time positions.
Benefits include:
- Private Medical, Vision and Dental Insurance
- Travel Medical Insurance
- Group Pension Scheme
- Group Life Assurance and Income Protection Schemes
- Paid Parental Leave
- Parking and Commuter Benefits
How we rate this
Campus ML Research Engineer (Full-Time) at Jump Trading rates 95 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.
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. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Walk me through how you've used PyTorch in your day-to-day work.
- What are the limits of TensorFlow that you've run into, and how did you work around them?
- What's a project where you used Jax hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: AI Research, PyTorch, TensorFlow, 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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