IC Resources
Senior ML Systems Engineer
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Senior ML Systems Engineer
Machine Learning Systems Performance Modeller
Hands-on Technical Role at the Frontier of Large-Scale ML Infrastructure
We’re partnering with a well-funded, research-driven organisation to fill a critical position for someone passionate about performance modelling, distributed systems, and hardware-specific optimisations—with direct impact on architecture decisions at scale.
Responsibilities
-
Build simulation models that accurately represent:
- Compute behaviour
- Memory characteristics
- Interconnect systems
- Communication performance across large-scale ML systems
-
Develop proprietary tools for:
- Simulating training and inference workloads
- Emulating execution across distributed accelerator clusters
-
Model sophisticated distributed execution patterns including:
- Collectives (e.g., Allreduce, Allgather)
- Synchronisation mechanisms
- Communication bottlenecks
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.
-
Run and analyse real-world experiments and benchmarks to:
- Calibrate simulation models
- Validate results on deployed ML systems
-
Perform deep performance analysis covering:
- End-to-end throughput
- Latency characteristics
- Scaling efficiency
- Cost/performance tradeoffs
-
Collaborate cross-functionally to translate findings into design recommendations with teams spanning:
- Hardware engineering
- Software development
- Network infrastructure
- Machine Learning (ML)
Requirements
Academic Background
- Master’s or PhD in:
- Computer Science (CS)
- Electrical Engineering
- Computer Engineering
- or field directly related to ML systems
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Technical Skills & Experience
-
Deep background in:
- ML systems architecture
- Distributed systems engineering
- Performance modelling
- Simulation tool development
-
Proven ability to analyse and interpret:
- Compute behaviour
- Communication patterns
- Memory utilisation in large-scale ML systems
-
Hands-on experience with:
- Benchmarking
- Profiling
- Measurement frameworks for ML training/inference systems
-
Expertise with distributed training techniques:
- Data parallelism
- Tensor parallelism
- Pipeline parallelism
- Collective optimisations and synchronisation primitives
-
Proficiency in core development languages:
- Python
- C++
- Rust
Inquires and applications should be sent to Charles Duran.
“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
Skills
Location