Machine Learning Performance Engineer at SambaNova Systems

Location: San Jose, California
Type: Full-time
Posted: Jun 4, 2026

Description

SambaNova is looking for an experienced ML Performance Engineer to optimize and scale foundation models on their reconfigurable dataflow platform. The role involves working with advanced models like DeepSeek R1 and GPT OSS to improve throughput, latency, and efficiency. This position bridges deep learning and systems performance, requiring collaboration across various layers to deliver high-performance AI inference.

Required Skills

Deep learning model development
Compiler, runtime, or kernel-level optimization
Software-hardware co-design
Systems performance tuning
Python
C++
Algorithms
Data Structures
Numerical Computing
PyTorch
TensorFlow
JAX

Additional Information

Minimum Education: Bachelor's or higher degree in computer science, electrical engineering, or a related field (e.g., applied mathematics, physics, or statistics)
Required Previous Experiences: 3+ years of experience in one or more of the following areas:
Deep learning model development and performance optimization
Compiler, runtime, or kernel-level optimization
Software–hardware co-design or systems performance tuning
Preferred Qualifications: Hands-on experience with LLM or multimodal model training and inference.
Background in large-scale distributed training, continuous batching, and high-throughput inference systems.
Familiarity with quantization, graph optimization, kernel fusion, and model partitioning.
Experience with frameworks such as DeepSpeed, Megatron, vLLM, or TensorRT.
Strong GPU programming skills (CUDA, Triton, or OpenCl); experience with cuDNN, cuBLAS, or similar libraries is a plus.
Knowledge of memory hierarchy optimization, caching, and scheduling for large-scale model execution.
Publication record or open-source contributions in ML systems or performance optimization is a plus.