Senior Research Scientist – Machine Learning Systems, Efficiency Engineer

Responsibilities

• Design and optimize high‑throughput, low‑latency inference systems
• Write and maintain high‑performance GPU kernels
• Conduct deep performance analysis using tools such as PyTorch Profiler
• Partner with infrastructure teams to design scalable distributed systems
• Establish and track efficiency metrics and build benchmarking frameworks
• Serve as a trusted technical advisor to research and product teams

• Master’s or PhD in Computer Science, Electrical Engineering, or related field
• Hands‑on experience implementing and scaling large‑scale inference or serving workloads
• Strong understanding of GPU architecture
• Proficiency in Python and C++
• Familiarity with CUDA or Triton for performance‑critical workloads
• Demonstrated ability to make engineering decisions based on rigorous measurement and benchmarking
• Hard skills: GPU kernels, high‑throughput systems, low‑latency systems, performance analysis, Python, C++, CUDA, Triton, benchmarking frameworks, inference workloads
• Soft skills:
  
  technical advisor, collaboration, decision making, measurement
• Certifications:
  
  Master’s in Computer Science, PhD in Computer Science, Master’s in Electrical Engineering, PhD in Electrical Engineering