Jobs at Permute

Productionize and optimize ML systems for AI reasoning over structured data. Responsibilities include improving training and inference performance, porting workloads from CPU to GPU, building training and deployment infrastructure, developing experimentation and observability tools, and implementing new model architectures and fine-tuning methods using Python and PyTorch. The role requires strong ML research, systems engineering, software architecture, optimization, and experimental design skills.

Designs, implements, and deploys customer-specific technical solutions for complex financial workflows. Responsibilities include gathering requirements, designing architectures, building integrations, data pipelines, APIs, and application workflows, troubleshooting technical issues, and collaborating with product and engineering teams. The role combines coding, financial workflow analysis, customer communication, rapid prototyping, and identifying reusable product capabilities in a fast-moving startup environment.

Design, build, and deploy production-grade AI systems including LLM-powered agents, tool-integration pipelines, model evaluation and monitoring infrastructure, and agent orchestration. Collaborate with product, research, and engineering to prototype, optimize, and productionize RL and agent orchestration approaches while ensuring reliability and scalability in a fast-moving startup.

Build and operate scalable data pipelines, ingestion, transformation, and storage to support LLMs and ML systems. Create tooling for data quality, monitoring, and observability. Collaborate with engineering, product, and ML teams to enable experimentation, training, evaluation, and reliable production AI features in a fast-moving startup.