OpenSource
Senior Machine Learning Engineer
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Senior ML Platform Engineer
Location: London - hybrid, with three days per week in the office
An established quantitative research and trading business is looking for a Senior ML Platform Engineer to shape its research and machine learning infrastructure. This newly created role offers the opportunity to improve how quantitative researchers build, test and deploy models. You’ll make the systems around their work faster, more reliable and easier to maintain, helping them spend more time on research.
The role
Working closely with quantitative research, development, infrastructure and data teams, you’ll own improvements from identifying the problem through to delivery, operation and measuring the results.
Your responsibilities will include:
- Designing and improving platform architecture across on-premises and cloud compute.
- Building shared tools that reduce repetitive engineering work for researchers.
- Profiling and optimising simulation, model training, validation and back-testing workloads.
- Improving CPU, memory and I/O performance, alongside effective use of parallel processing.
- Creating reliable routes from research notebooks to production, supported by testing, monitoring and reproducible environments.
- Evaluating and introducing technologies where they offer measurable benefits.
- Documenting technical decisions and sharing knowledge across teams.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
About you
You’ll bring strong Python skills and a track record of making numerical or data-intensive systems measurably faster and more reliable. You should also have:
- Experience designing and owning systems used by researchers, data scientists or analysts.
- Practical experience with profiling, vectorisation, parallelism and tools such as Cython or Numba.
- Sound architectural judgement, including knowing when to build, reuse or retain existing solutions.
- Strong production engineering practices, including testing, observability, continuous integration and reproducible environments.
- The confidence to define your own direction when requirements are open-ended.
- Clear communication skills and the ability to bring colleagues with you through technical changes.
- Experience with simulation or backtesting, ML pipelines, MLOps, quantitative finance, trading, Docker or Kubernetes would be useful.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Technology
The environment includes Python, Cython, pandas, NumPy, SciPy, PyArrow, Jupyter, Parquet, Snowflake, PostgreSQL, GitLab and Bash, alongside some legacy HDF5 systems.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Location