Staff ML Engineer: Lead Multimodal & LLM Systems (Equity)

Pinterest

Seattle (WA)

Hybrid

USD 189,000 - 390,000

Full time

6 days ago
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Benefits offered by this job

Equity

Job summary

Pinterest is seeking a Staff Machine Learning Engineer / Technical Lead to drive the technical direction for foundational ML capabilities in visual representation learning, multimodal content understanding, and LLM-based personalization. You will lead cross-functional teams across research, ML, and engineering to deliver scalable content understanding solutions.

You will guide ambitious research, productionization, and adoption efforts, mentoring engineers and scientists while shaping roadmaps

Qualifications

  • 7+ years of industry experience, including 2+ years of tech leading teams.
  • MS or PhD in computer science, machine learning, or equivalent experience.
  • Publications at top ML conferences or open-source ML experience.

Responsibilities

  • Set the technical direction for foundational ML capabilities across visual representation learning and multimodal content understanding.
  • Lead high-impact scientific and technical initiatives from problem definition through productionization.
  • Build reusable embeddings and ML infrastructure while advancing VLMs, LLMs, and sequence modeling techniques.
  • Partner with Product, Data Science, Applied Science, and Engineering to translate capabilities into product outcomes.
  • Establish rigorous practices for modeling, data pipelines, distributed training, inference and evaluation.

Skills

Distributed training
Distributed tooling
Leadership
Publications
LLMs & VLMs
Cross-functional collaboration

Education

MS or PhD in CS/ML

Tools

Spark
Hive
MapReduce

Job description

Pinterest is seeking a Staff Machine Learning Engineer / Technical Lead to drive the technical direction for foundational ML capabilities in visual representation learning, multimodal content understanding, and LLM-based personalization. You will lead cross-functional teams across research, ML, and engineering to deliver scalable content understanding solutions.

You will guide ambitious research, productionization, and adoption efforts, mentoring engineers and scientists while shaping roadmaps

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