Senior Software Engineer, Machine Learning Infrastructure, Generative AI

What you'll do

• Design and architect infrastructure for real-time GPU serving, high-throughput batch inference, and model fine-tuning.
• Manage the open-weights serving stack including LLM Gateways, agent gateways, evals infrastructure, and cost attribution.
• Optimize GPU utilization and performance to reduce costs and latency for large-scale inference tasks.
• Build scalable systems that support rapid experimentation while meeting production standards for reliability and monitoring.
• Set technical direction for emerging technologies like reinforcement learning, agent optimization, and post-training techniques.
• Mentor engineers and collaborate with cross-functional teams to turn GenAI capabilities into durable platform primitives.

What we're looking for

• Hold a B.S., M.S., or PhD. in Computer Science or an equivalent degree.
• Possess 6+ years of industry experience in software engineering.
• Demonstrate deep backend engineering fundamentals, specifically in Python and distributed systems.
• Have a track record of designing and owning production services, APIs, data pipelines, or ML infrastructure at scale.
• Experience operating systems in production including observability, debugging, reliability, incident response, and performance/cost optimization.
• Possess hands-on experience with LLM inference and fine-tuning of open-weight models in production.
• Demonstrate technical leadership by leading design in ambiguous areas and mentoring other engineers.
• Proficiency in using AI coding tools throughout the full software development lifecycle.