Software Engineer

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

We are looking for Software Engineers to join our team. This is a specialized, high-impact role at the intersection of high-performance computing (HPC) and Large Language Model (LLM) engineering. You will define the roadmap, drive key technical decisions, and take full ownership of the future of this work.

• Benchmarking: Evaluate, run, and automate standard LLM quality benchmarks (GSM8K, MMLU) alongside custom performance suites for specific workloads (e.g., long-context window, KV cache reuse, disaggregated serving).
• DevEx Improvement: Develop and maintain internal GPU-enabled development environments (similar to GitHub Codespaces).
• Tool Development: Build and contribute to open-source tools such as InferenceMAX and genai-bench to automate model evaluation, benchmarking, and analysis.
• System Profiling: Use profilers like PyTorch Profiler, NVIDIA Nsight Systems, and py-spy to collect performance profiles, identify bottlenecks, and debug the 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 and build release workflow automation for the model runtimes stack.
• Optimization Automation: Build tools to find the 'Pareto frontier'—identifying the best configuration (latency vs. cost vs. quality) for a given model and workload.

• This is a mid-senior, high leverage role. We care about technical depth, strong communication skills to drive cross-team efforts, ability to navigate vague requirements, and mentoring other engineers.
• A love for systems and hardware: understanding 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-testing and fuzzy testing.
• Mathematical curiosity: desire to understand the underlying math of Transformers and how it translates into FLOPs and memory requirements.
• Technical toolkit: familiarity with Python, eagerness to master the NVIDIA software stack; C++ familiarity is good to have.

• Direct impact: your tools will be the gatekeeper for what defines 'good' performance for customers.
• Deep learning: gain world-class expertise in GPU orchestration and LLM inference.
• High ownership: as the lead of a small team, you will have autonomy to build tools from scratch and contribute to open-source projects.

• 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.

Apply via the provided application link.