F · via a16z Speedrun 4d ago Senior Software Engineer, Machine Learning Infrastructure & Automation Fal

Position: F Open role · via a16z Speedrun 4d ago Senior Software Engineer, Machine Learning Infrastructure & Automation Fal US
# Senior Software Engineer, Machine Learning Infrastructure & Automation $170k–230k Remote-friendly Remote - USAAT A GLANCE Senior engineer building ML CI/CD infrastructure, automation, and developer tooling to accelerate model development and deployment at scaleLEVELsenior
· 5+ yrsKEY SKILLSPythonCI/CDGitHub Actions Docker Py Torch NVIDIA GPUsDistributed systems

Automated testing

Model serving

Observability

Infrastructure-as-code Performance benchmarking

Kubernetes

Cloud infrastructure WHAT YOU'LL DO
* Design and maintain automated testing, validation, and deployment pipelines for ML models and inference services
* Reduce CI execution times through intelligent parallelization, caching, and efficient compute resource usage
* Develop systems for automated model validation and quality regression detection across different GPU architectures
* Build continuous performance testing to detect regressions in inference latency, throughput, and GPU utilization
* Create automated pricing, billing, and deployment validation systems
* Develop AI-powered agentic workflows to diagnose CI failures and propose fixes
* Improve deployment reliability with automated safeguards, verification, and rollback mechanisms
* Identify and automate repetitive engineering tasks to eliminate toilTHE ROLE fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.

As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.

About this role

Help fal's ML team move faster by building the automation, infrastructure, and developer tooling that makes developing, testing, and deploying generative AI models seamless. You'll own and improve the CI/CD systems supporting our rapidly growing collection of ML models and inference pipelines. Your focus will be on eliminating manual work, accelerating development cycles, and building reliable systems that allow ML engineers to ship new models and optimizations with confidence.

This is a high-impact engineering role where you'll work closely with our Applied ML and ML Performance teams. You'll build everything from automated model validation and performance benchmarking to AI-powered development workflows that help engineers iterate faster. The ideal candidate thinks beyond traditional CI/CD and sees automation as a force multiplier for the entire engineering organization.

What you’ll do
* Own ML CI/CD infrastructure Design, build, and maintain automated testing, validation, and deployment pipelines for our ML models and inference services.
* Accelerate development cycles.

Dramatically reduce CI execution times through intelligent parallelization, caching, test selection, and efficient use of compute resources.
* Build automated model validation.

Develop systems that test model outputs, detect quality regressions, and validate changes across different models, GPU architectures, and configurations.
* Automate performance benchmarking. Build continuous performance testing that detects regressions in inference latency, throughput, GPU utilization, and cost.
* Build automated pricing and deployment checks. Ensure model pricing, billing configurations, API schemas, and deployments are validated automatically before reaching production.
* Extend our agentic engineering…