What is the salary for this Senior ML Performance Engineer role?

Salary information is not publicly listed for this position. Apply directly to discuss compensation with Lemurian Labs.

Where is this Senior ML Performance Engineer position located?

This is an on-site position at Lemurian Labs located in SF Bay Area.

How do I apply for this Senior ML Performance Engineer job at Lemurian Labs?

Click the 'Apply' button on this page to be redirected to Lemurian Labs's application portal. Make sure to have your resume ready and tailor your application to highlight relevant experience.

What is Lemurian Labs?

Lemurian Labs is actively hiring for Engineering roles. Visit the company page to see all open positions and learn more about working at Lemurian Labs.

Senior ML Performance Engineer

Lemurian Labs SF Bay Area 1 day ago

engineering

About Us

At Lemurian Labs, we're on a mission to bring the power of AI to everyone—without leaving a massive environmental footprint. We care deeply about the impact AI has on our society and planet, and we're building a solid foundation for its future, ensuring AI grows sustainably and responsibly. Innovation should help the world, not harm it.

We are building a high-performance, portable compiler that lets developers "build once, deploy anywhere." Yes, anywhere. We're talking about seamless cross-platform compatibility, so you can train your models in the cloud, deploy them to the edge, and everything in between—all while optimizing for resource efficiency and scalability.

If the idea of sustainably scaling AI motivates you and you're excited about making AI development both powerful and accessible, then we'd love to have you. Join us at Lemurian Labs, where you can have fun building the future—without leaving a mess behind.

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.

What You'll 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

Investigate performance bottlenecks using profiling tools (ROCm profilers, GPU traces, system-level monitoring) and work with the compiler team to drive optimizations

Create dashboards and reporting that provide clear visibility into performance trends, regressions, and wins

Collaborate cross-functionally with compiler engineers, ML engineers, and DevOps to ensure performance testing is integrated into our development workflow

Document best practices for performance testing and optimization of ML workloads on GPU hardware

What You'll Bring

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)

Strong programming skills in Python and C/C++

Proven track record of building performance testing infrastructure or benchmarking platforms from scratch

Experience with ML frameworks (PyTorch, TensorFlow, ONNX Runtime, vLLM, TensorRT-LLM, etc.)

Proficiency with profiling and debugging tools for GPU workloads

Strong analytical skills with the ability to design experiments, analyze results, and communicate findings clearly

Experience with CI/CD systems and test automation frameworks

Nice to Have

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

Obsessive 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

Salary depends on experience and geographical location.

This salary range may be inclusive of several career levels and will be narrowed during the interview process based on a number of factors, such as the candidate’s experience, knowledge, skills, and abilities, as well as internal equity among our team.

Additional benefits for this role may include: equity, company bonus opportunities, medical, dental, and vision benefits; retirement savings plan; and supplemental wellness benefits.

Lemurian Labs ensures equal employment opportunity without discrimination or harassment based on race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, disability, national origin, marital or domestic/civil partnership status, genetic information, citizenship status, veteran status, or any other characteristic protected by law.

EOE