Staff Machine Learning Engineer leading a team focused on content recommendations for Pinterest. Driving multi-quarter technical vision and hands-on ML systems design and execution.
Responsibilities
Own the long‑term architecture, roadmap, and execution for source discovery, acquisition optimization, and content understanding.
Lead design reviews, set engineering standards, and drive cross‑team alignment with Product, Data, and Infra.
Mentor and uplevel MLEs through technical direction, pairing, and reviews.
Train/fine‑tune LLMs and NLP models for classification, extraction, and instruction‑following; design eval loops and guardrails.
Design features and frameworks for sharing features across models.
Productionize models for large-scale inference; drive latency, reliability, and cost efficiency (quantization, distillation, caching).
Establish offline/online evaluation, gold sets, and automated regressions; run A/B and canary/shadow launches.
Work with human and automated labeling sources to define data labeling standards.
Partner on data strategy, labeling/weak supervision, and feedback loops to expand coverage and improve precision/recall.
Define and meet SLOs for data quality, model performance, and serving reliability; lead incident playbooks and postmortems.
Measure and drive downstream impact on revenue and engagement.
Requirements
5+ years building ML products end‑to‑end, including 2+ years as a tech lead driving multi‑quarter roadmaps and cross‑functional execution.
Deep hands‑on experience with NLP/LLM training and inference (PyTorch, Python); strong grounding in evaluation, prompt/data design, and fine‑tuning.
Proven track record shipping models at scale: feature/data pipelines, online serving, monitoring/observability, and cost/perf trade‑offs.
Strong software engineering in Python with an eye for software engineering best practices.
Experience mentoring senior engineers and influencing partner teams.
Masters or PhD in ML related studies.
LLM efficiency techniques (LoRA/adapters, distillation, quantization, prompt caching) and cost control strategies.
MLOps at scale with tools like Airflow, Spark/Presto, Triton, vLLM.
Benefits
This position is not eligible for relocation assistance
Visit our PinFlex page to learn more about our working model.
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