WHAT YOU'LL DO
GPU Cluster & Infrastructure
Own our H200 GPU cluster end to end: Kubernetes and Slurm for training and inference workloads, with multi-tenant scheduling, quotas, and resource isolation
Keep large distributed training runs healthy: node health checks, NCCL and interconnect debugging, automated job recovery, and checkpoint management
Track and optimize GPU utilization and cost across training and inference, with dashboards and budget alerting
Manage infrastructure-as-code and provisioning for GPU environments
Define and monitor SLIs/SLOs for cluster availability and production model serving
Deployment & Serving
Deploy LLMs to production using vLLM or SGLang, with CI/CD, model versioning, and safe rollouts and rollbacks
Monitor serving latency, throughput, errors, and cost, and act on regressions
ML Acceleration
Profile training and inference end to end (PyTorch Profiler, Nsight Systems, Nsight Compute) to find and remove bottlenecks
Improve training throughput and MFU: parallelism strategies (FSDP, tensor and pipeline parallelism), communication/compute overlap, mixed precision and FP8, activation checkpointing, torch.compile
Optimize inference: quantization (FP8, INT8, INT4), speculative decoding, prefix caching, continuous batching, KV cache tuning, and parallelism layouts
Write or integrate fused and custom kernels (Triton, CUDA) where off-the-shelf implementations fall short
Build benchmarking tooling so every optimization ships with measured gains
Enablement & Best Practices
Partner with ML engineers and researchers to make training and serving efficient by default
Establish best practices for using the cluster and guide teams in their adoption
MINIMUM QUALIFICATIONS
5+ years in ML infrastructure, MLOps, HPC, or platform engineering with focus on GPU workloads
Hands-on experience operating multi-node GPU clusters with Kubernetes and/or Slurm, including debugging hardware, networking (NCCL, InfiniBand/RoCE), and job failures
Production experience deploying and optimizing LLM inference with vLLM, SGLang, or TensorRT-LLM
Proven track record of profiling and accelerating GPU workloads, with measured results in throughput, latency, MFU, or cost
Solid understanding of monitoring and observability for GPU systems (Prometheus, Grafana, DCGM, or similar)
Naturally curious with a track record of proactively identifying and implementing improvements
PREFERRED QUALIFICATIONS
Experience writing custom kernels in Triton or CUDA, and familiarity with fused kernels such as FlashAttention
Performance tuning of distributed training frameworks: FSDP, Megatron-LM, or DeepSpeed
Experience with low-precision training and inference (**FP8**, INT4) and model compression for production deployment
Deep knowledge of GPU architectures: memory hierarchy, tensor cores, roofline analysis
Experience with multi-tenant GPU scheduling and fair-share resource allocation
Contributions to open-source projects such as vLLM, SGLang, PyTorch, or Triton
WHAT WE OFFER
Critical infrastructure ownership for high-impact AI projects that are strategically vital to the company, with direct visibility to senior leadership including the CEO
State-of-the-art GPU infrastructure: H200 fleet, vLLM serving stack, and the freedom to optimize it end to end
Expert ML team who have released top Hugging Face models, published at NeurIPS, and built production systems that will run on your infrastructure
Significant autonomy in choosing tools and shaping our infrastructure and performance strategy
Modern tooling: Latest ML frameworks, coding assistants, best-in-class development environment
Hybrid work model with our Amsterdam office - home to the AI House, bringing together 200+ AI professionals through events and collaborations
Competitive compensation, top-spec MacBook Pro, and an environment genuinely built for professional growth and learning
If you're excited to own the GPU infrastructure behind cutting-edge LLMs and make every training run and every request faster, let's talk.
Why Prosus?
At Prosus, your colleagues include 60,000 AI agents… and your job is to figure out what that actually means. We're one of the largest operators of agentic AI on the planet, inside a $100B+ portfolio across 100+ companies and two billion people. The humans here own what AI can't do alone: judgment, creativity, and the call on what gets built next.
Own the impact. Work the ecosystem. Earn your growth. Build with backing.
Curious about our perks and benefits? Take a look at this page https://prosusbenefits.com/.
Our Diversity & Inclusion Commitment
We respect the dignity and human rights of individuals and communities wherever we operate in the world. Building an inclusive workplace where everyone feels welcome and can thrive is critical for us. We provide access to education, which helps everyone understand the important role they play and the positive impact they can have.
Want to know more about life at Prosus? Explore our culture and values https://www.prosus.com/the-prosus-way.
