PlaidSan Francisco, CALead technical strategy and development of Plaid’s financial foundation models as a Staff ML Engineer. Own full ML lifecycle from pretraining and data curation to production serving, evaluation, and cross-team integration while mentoring engineers and setting technical standards.
Staff engineer owns large product areas in enterprise GenAI platform, working across backend, frontend, LLMs, and ML models. Solves scalability challenges with 7+ years experience in Python/JS, Kubernetes, and cloud providers.
Build and scale eval systems, fine-tuning pipelines, agent-first infrastructure, and data platforms that power frontier AI labs at Labelbox. Requires full-stack prototyping expertise, strong architecture judgment, daily use of coding agents, and deep TypeScript/Python proficiency (7+ years implied by Staff level).
Senior individual contributor architecting and scaling agentic LLM systems that turn messy manufacturing data into reliable root-cause insights. Owns orchestration, retrieval, evaluation, and guardrails for non-deterministic production systems.
Conduct optimization research and implement large-scale constrained optimization models that drive real-time trading decisions, working across the full research lifecycle from theory to production. Requires PhD-level coursework and strong applied research background in optimization.
New/recent PhD to own RL and post-training for large-scale omni models. Build and scale the full RL/post-training stack including rollout, optimization, reward modeling, and evaluation for real-time audiovisual AI.