AI Systems Performance Engineer - New Graduate

SambaNova is a pioneering company in the AI sector, offering a full-stack generative AI platform. They are seeking an AI Systems Performance Engineer to optimize advanced AI models on their dataflow platform, collaborating with various engineering teams to enhance system performance and efficiency.

What you'll do:

• Bring up cutting-edge foundation models, including LLMs and multimodal models, on the SambaNova platform through the SambaNova software stack
• Analyze and profile model execution to identify performance bottlenecks across model, compiler, runtime, and hardware layers
• Optimize AI workloads for throughput, latency, memory efficiency, and scalability
• Collaborate with machine learning, compiler, runtime, and hardware engineers to develop high-performance AI applications
• Explore and integrate new techniques in model architecture, quantization, scheduling, caching, and memory optimization
• Develop tools, benchmarks, and performance analysis methodologies for large-scale AI inference
• Investigate new model architectures and translate research advances into efficient implementations on production AI systems
• Contribute ideas for dataflow, scheduling, and system optimizations for both single-node and distributed inference

What they're looking for:

• Bachelor's or Master's degree in computer science, electrical engineering, computer engineering, or a related technical field (e.g., applied mathematics, physics, or statistics), completed or expected before the start date
• Strong programming skills in Python, C++, or a similar programming language
• Solid foundations in algorithms, data structures, computer architecture, operating systems, or parallel computing
• Familiarity with deep learning and at least one major ML framework, such as PyTorch, TensorFlow, or JAX
• Strong analytical and problem-solving skills, with an interest in understanding and optimizing system performance
• Ability and enthusiasm to learn across machine learning, software systems, and hardware
• Coursework, research, internship, or project experience in machine learning systems, computer architecture, compilers, distributed systems, or high-performance computing
• Hands-on experience with LLMs, multimodal models, or transformer architectures
• Familiarity with model inference, KV cache, batching, quantization, or distributed execution
• Experience with GPU or accelerator programming using CUDA, Triton, OpenCL, or similar technologies
• Familiarity with frameworks such as vLLM, DeepSpeed, Megatron, or TensorRT
• Understanding of memory hierarchy, caching, parallelism, or scheduling

Benefits:

• Equity
• 95% premium coverage for employee medical insurance
• 77% premium coverage for dependents
• Health Savings Account (HSA) with employer contribution
• Dental insurance
• Vision insurance
• Short/Long term Disability insurance
• Basic Life insurance
• Voluntary Life insurance
• AD&D insurance plans