MixpanelSan Francisco, CABuild scalable AI platform infrastructure including agent orchestration frameworks, evaluation systems, and high-performance serving layers to accelerate AI development and deployment at Mixpanel and for customers. Requires 2+ years software engineering experience with hands-on LLM/agent integration and full-stack fundamentals.
Total Target Cash Compensation (TTCC): $188,000–$254,000 USD (includes base and variable compensation; benchmarked to SF Bay Area).
Benefits:
Build and operate scalable ML training frameworks, distributed infrastructure, and model lifecycle tools to power foundational models, reinforcement learning, and other ML use cases across Zoox's autonomous driving teams. Requires 2+ years ML infrastructure experience with PyTorch, DeepSpeed, JAX, Ray and AWS.
Designs datasets, evaluation rubrics, and reward signals for RLHF/RLVR pipelines to expose model failure modes and improve frontier AI capabilities. Partners with AI labs; requires 1-4 YOE and passion for data-driven model behavior.
Leads end-to-end delivery of multi-agent AI systems for enterprise clients, analyzing workflows, building Python-based integrations with systems like SAP and Salesforce, and ensuring production deployment. Requires 1-3 years experience in data science or solutions engineering, Python proficiency, and strong communication skills.
Partners with sales to drive technical sales of AI/ML infrastructure, leading demos, POCs, and solutions for enterprise customers. Requires 2+ years software engineering, AI/ML expertise, and strong communication skills.
Research Engineer building and deploying production conversational AI models and agents at Decagon. Improve instruction following, retrieval, memory, and long-horizon task completion; take research prototypes to measurable production impact using LLMs and ML tooling.