Cloud Software Architect

2 days ago


Saddar Town, Pakistan beBeeSoftware Full time $150,000 - $200,000

Seeking a seasoned software engineer to spearhead the development and optimization of our inference systems. The ideal candidate will have expertise in designing and implementing distributed inference platforms, optimizing runtime and infrastructure layers for optimal model performance, and building native cross-platform inference support across NVIDIA and AMD GPUs.

Key Responsibilities:
  • Design and implement a distributed inference platform for serving large language models
  • Optimize runtime and infrastructure layers of the inference stack for best model performance
  • Build native cross-platform inference support across NVIDIA and AMD GPUs for various model architectures
  • Contribute to open-source inference engines to improve their performance on DigitalOcean cloud
  • Develop tooling and observability to monitor system health and build auto-tuning capabilities
  • Build benchmarking frameworks to test model-serving performance and guide system and infrastructure tuning efforts
  • Mentor engineers on inference systems, GPU infrastructure, and distributed inference best practices
Requirements:
  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field
  • Experience in building distributed systems with Kubernetes, gRPC, Go, Python, and GPU programming with CUDA, ROCm
  • Experience with L3-L7 network protocols, block storage, object storage, and multi-tenant systems - identity management and tenant isolation
  • Proven track record defining and achieving performance KPIs (latency, throughput, cost)
Preferred Qualifications:
  • Experience with one or more inference engines: vLLM, SGLang, Modular etc
  • Familiarity with one or more distributed inference serving frameworks - llm-d, NVIDIA dynamo, Ray Serve etc
  • Knowledge of distributed inference optimization techniques - tensor/data parallelism, KV cache optimizations, smart routing etc
  • Familiarity with common LLM architectures and inference optimization techniques (e.g. continuous batching, quantization etc)
  • Experience with GPU Interconnect technologies like NVlink, XGMI, RoCE
  • Open-source contributions to inference libraries, frameworks, model kernels etc
What We Offer:

Opportunity to work with a dynamic team dedicated to revolutionizing cloud computing and AI

Support for career development with reimbursement for relevant conferences, training, and education

Access to LinkedIn Learning's 10,000+ courses to support continued growth and development



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