Staff Software Engineer, ML Performance & Systems

fal; San Francisco (CA); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

Competitive salary and equity

Visa sponsorship

Health, dental, and vision insurance

Regular team events

Job summary

A tech company in San Francisco is looking for a Staff Software Engineer to enhance model performance for generative media models. The ideal candidate will design advanced model serving architectures, develop performance tools, and collaborate with the Applied ML team. Offering a competitive salary of $180,000 - $250,000 with equity and comprehensive health benefits, this position provides substantial growth opportunities.

Qualifications

• Strong foundation in systems programming with expertise in identifying and fixing bottlenecks.
• Deep understanding of cutting edge ML infrastructure stack including model compilation, quantization, and serving architectures.
• Proficient in Triton or willingness to learn with comparable experience in lower-level accelerator programming.

Responsibilities

• Help maintain frontier position on model performance for generative media models.
• Design and implement novel approaches to model serving architecture.
• Develop performance monitoring and profiling tools.

Skills

Systems programming expertise

ML infrastructure stack knowledge

Multi-dimensional model parallelism

Triton proficiency

Tools

PyTorch

TensorRT

Nvidia systems

Job description

Staff Software Engineer, ML Performance & Systems

Help fal maintain its frontier position on model performance for generative media models. Design and implement novel approaches to model serving architecture on top of our in-house inference engine, focusing on maximizing throughput while minimizing latency and resource usage. Develop performance monitoring and profiling tools to identify bottlenecks and optimization opportunities. Work closely with our Applied ML team and customers (frontier labs on the media space) and make sure their workloads benefit from our accelerator.

Key Responsibilities

• Help fal maintain its frontier position on model performance for generative media models.
• Design and implement novel approaches to model serving architecture on top of our in-house inference engine, focusing on maximizing throughput while minimizing latency and resource usage.
• Develop performance monitoring and profiling tools to identify bottlenecks and optimization opportunities.
• Work closely with our Applied ML team and customers (frontier labs on the media space) and make sure their workloads benefit from our accelerator.

Requirements

• Strong foundation in systems programming with expertise in identifying and fixing bottlenecks.
• Deep understanding of cutting edge ML infrastructure stack (anything from PyTorch, TensorRT, TransformerEngine to Nsight), including model compilation, quantization, and serving architectures. Ideally following closely the developments in all these systems as they happen.
• Have a fundamental view of the underlying hardware (Nvidia based systems at the moment), and when necessary go deeper into the stack to fix bottlenecks (custom GEMM kernels with CUTLASS for common shapes).
• Proficient in Triton or willingness to learn with comparable experience in lower-level accelerator programming.
• New frontier: multi-dimensional model parallelism (combining multiple parallelism techniques like TP with context parallel / sequence parallel).
• Familiar with internals of Ring Attention, FA3, FusedMLP implementations.

What we offer at fal

• Interesting and challenging work
• Competitive salary and equity
• Employee-friendly equity terms (early exercise, extended exercise)
• A lot of learning and growth opportunities
• We offer visa sponsorship and will help you relocate to San Francisco.
• Health, dental, and vision insurance (US)
• Regular team events and offsite

Compensation

$180,000 - $250,000 + equity + comprehensive benefits package

Location

We are currently hiring in downtown San Francisco.