Software Engineer, Model Performance Systems

Baseten powers mission-critical inference for dynamic AI companies, enabling them to bring cutting-edge models into production. They are looking for early-career Software Engineers to build automated diagnostic tools for their AI infrastructure, focusing on performance benchmarking and system optimization.

What you'll do:

• Performance Benchmarking: Run and automate standard LLM quality benchmarks (GSM8K, MMLU) alongside custom performance suites for specific workloads (e.g., long-context window, KV cache reuse)
• Infrastructure Validation: Create automated acceptance tests for new GPU clusters across x86 and ARM systems, measuring GPU memory bandwidth, networking throughput, and multi-node networking performance
• Model Dev Experience: Develop and maintain internal GPU-enabled development environments (similar to GitHub Codespaces). You will ensure the team has seamless, high-performance "dev machines" optimized for model experimentation
• Tool Development: Build and contribute to tools such as InferenceMAX and genai-bench to automate model evaluation and optimization
• Deep Hardware Profiling: Use PyTorch Profiler and NVIDIA Nsight Systems to collect performance profiles, identify bottlenecks, and debug the NVIDIA compute/networking stack
• Monitoring & Observability: Develop real-time dashboards and alerts to monitor system health, model startup times, and runtime performance
• Continuous Integration: Automate performance testing via CI/CD pipelines to catch regressions in model setups before they hit production
• Optimization Automation: Build tools to find the "Pareto frontier"—identifying the absolute best configuration (latency vs. cost vs. quality) for a given model and workload

What they're looking for:

• A Love for Systems & Hardware: You aren't just interested in the AI; you want to understand GPU memory subsystems, InfiniBand, and how data moves across a cluster
• An Automation Mindset: You believe that if a task has to be done twice, it should be scripted. You have a passion for stress-testing and fuzzy testing to find the 'breaking point' of a system
• Mathematical Curiosity: A desire to understand the underlying math of Transformers and how it translates into FLOPs and memory requirements
• Interest in Optimization: You are excited to learn about (or already play with) quantization, speculative decoding, disaggregated serving, and kernel-level optimizations
• Technical Toolkit: Familiarity with Python, and an eagerness to master the NVIDIA software stack. C++ familiarity is good to have

Benefits:

• Offers Equity
• 100% coverage of medical, dental, and vision insurance for employee and dependents
• Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
• Paid parental leave
• Fertility and family-building stipend through Carrot
• Company-facilitated 401(k)
• Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.