About Us At Lemurian Labs, we're reimagining the foundations of computing to make AI accessible to everyone. Our mission is to remove the limits of scale, hardware, and cost that hold back innovation, so the people solving humanity's hardest problems can move faster.

We're building a new kind of software stack: a hardware-agnostic platform that makes every system — from a laptop to a supercomputer — feel like one seamless engine. Developers can write once, run anywhere, and get state-of-the-art performance across any chip, any cloud, at any scale. It's a complete rethink of how software and hardware interact — designed for the era beyond Moore's Law.

We're not looking for the comfortable or the conventional; we're looking for the bold. The engineers who crave frontier problems, who want to bend the limits of what's possible, who see infrastructure not as a constraint but as a canvas. If you want to build the foundation for the next era of AI and change what humanity can achieve in the process, join us.

The Role We're looking for a Senior ML Performance Engineer to architect and lead our Performance Testing Platform from the ground up. You'll be the technical authority on how we measure, validate, and optimize the performance of large language models (Llama 3.2 70B, DeepSeek, and others) before and after compiler optimization on modern GPU architectures.

This is a high-impact role where you'll directly influence our product quality and our customers' success. You'll work at the intersection of ML systems, GPU architecture, and performance engineering—building the infrastructure that proves our compiler delivers real value.

Here is what you will do:

• Design and build a comprehensive performance testing platform for evaluating LLM inference workloads across GPU clusters
• Define and implement the benchmarking methodology, metrics, and test suites that measure latency, throughput, memory utilization, power consumption, and model accuracy
• Establish baseline performance for unoptimized models (Llama 3.2 70B, DeepSeek, etc.) and validate post-optimization improvements
• Develop automated testing pipelines for continuous performance validation across compiler releases and model updates

Essential Skills and Experience:

• BS degree in computer science, computer engineering, electrical engineering, or equivalent practical experience
• 7+ years of experience in performance engineering, benchmarking, or systems engineering roles
• Deep understanding of ML inference workloads, particularly transformer-based models and LLMs
• Hands-on experience with GPU programming and optimization (CUDA, ROCm, or similar)

Preferred Skills and Experience:

• Masters or PhD degree in computer science, computer engineering, electrical engineering, or equivalent practical experience.
• Experience with AMD GPUs (Mi200/Mi300 series) and ROCm ecosystem
• Knowledge of compiler optimization techniques and their impact on performance
• Experience with distributed inference and multi-GPU workloads
• Familiarity with ML model quantization, pruning, and other optimization techniques
• Background in high-performance computing or systems-level optimization
• Experience with infrastructure-as-code (Kubernetes, Docker, Terraform)
• Contributions to open-source ML or systems projects

Personal Attributes:

• Meticulous about details — you notice the 2% regression that others miss
• Self-driven — you take ownership and don't wait for permission to solve problems
• Collaborative mindset — you work well across teams and help others succeed
• Passionate about sustainability — you care about making AI more efficient and environmentally responsible
• Clear communicator — you can explain complex technical concepts to both engineers and stakeholders

Lemurian Labs is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of gender identity, race, ethnicity, sexual orientation, disability status, age, or background.

Compensation depends on experience and geographic location and will be narrowed during the interview process. Additional benefits include equity, company bonus opportunities, medical, dental, and vision coverage, a retirement savings plan, and supplemental wellness benefits.