Software Engineer, Model Performance Systems

Stack

Responsibilities

• ▹Performance benchmarking: run and automate standard LLM quality benchmarks (GSM8K, MMLU) alongside custom performance suites (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 performance
• ▹Model dev experience: develop and maintain internal GPU-enabled development environments (similar to GitHub Codespaces)
• ▹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 before they hit production
• ▹Optimization automation: build tools to find the 'Pareto frontier' (latency vs. cost vs. quality) for a given model and workload

Requirements

• ▹A love for systems and hardware: interest in GPU memory subsystems, InfiniBand, and how data moves across a cluster
• ▹An automation mindset: if a task has to be done twice, it should be scripted; passion for stress- and fuzz-testing to find a system's breaking point
• ▹Mathematical curiosity: understanding the math of Transformers and how it translates into FLOPs and memory requirements
• ▹Interest in optimization: quantization, speculative decoding, disaggregated serving, kernel-level optimizations
• ▹Familiarity with Python and eagerness to master the NVIDIA software stack

Nice to have

• ▹C++ familiarity

Soft skills

What we offer

• ▹Competitive compensation, including meaningful equity
• ▹100% coverage of medical, dental, and vision insurance for employee and dependents
• ▹Flexible PTO policy including company-wide Winter Break (offices 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

About the company

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, Baseten enables companies operating at the frontier of AI to bring cutting-edge models into production. The company is growing quickly and recently raised a $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital.