Manager II, Machine Learning Engineering-Content Foundation
About this role
The Content Foundation ML team builds foundational content understanding capabilities that support Discovery, Search, Growth, and Ads by generating high-quality, reusable semantic signals from platform content. As a Manager II for Machine Learning Engineering, leadership involves guiding a team of engineers and applied scientists through the design of scalable systems, large multimodal models, and data infrastructure. The position requires driving technical direction, managing project execution, and collaborating closely with product and data science groups to deliver robust personalization features across Pinterest surfaces.
This role suits an experienced engineering leader who combines strong technical expertise in machine learning with a proven ability to mentor multidisciplinary teams. Candidates should excel at navigating ambiguous technical challenges, setting multi-quarter roadmaps, and aligning cross-functional stakeholders on priorities. Someone who thrives in a collaborative environment and has a deep understanding of generative AI, large language models, and distributed systems will find success here.
What you will do
- Lead, mentor, and grow a team of engineers and applied scientists focused on foundational content understanding signals and infrastructure.
- Set the long-term technical vision for semantic signal generation, reusable foundational layers, and scalable model-powered systems.
- Partner closely with product, data science, and downstream engineering teams to ensure signals drive measurable impact across Pinterest products.
- Manage project execution, roadmap planning, technical decision-making, risk mitigation, and progress updates to achieve business goals.
- Solve complex technical problems related to leveraging large language models and vision-language models for semantic content understanding.
- Improve inference throughput, freshness, and serving efficiency to handle millions of new pins and evolving content daily.
- Build robust monitoring, evaluation, and debugging systems to ensure signal quality, accessibility, latency, and scale.
What you need
- Bring 7 or more years of industry experience, which includes at least 2 years of management experience.
- Hold a Master's degree in computer science, computer engineering, or possess equivalent work experience.
- Demonstrate publication history at top machine learning and data mining conferences such as NeurIPS, ICML, KDD, or SIGIR.
- Possess hands-on experience with large-scale distributed training and inference for large language models and vision-language models.
- Utilize distributed tooling for machine learning data pipelines including Hadoop and Spark.
- Show proven technical leadership across machine learning and data systems, including setting direction for multi-quarter roadmaps.
- Exhibit excellent cross-functional communication and collaboration skills to build strong partnerships with diverse stakeholder groups.
Benefits
- Equity eligibility
Skills and tech stack
Questions candidates ask
What is the remote work and office policy for this role?
This role can be situated anywhere in the USA and utilizes a flexible working model called PinFlex. Employees are required to be in the office for in-person collaboration 1 to 2 times per quarter.
What is the salary range for this position?
The base salary range for this position is $222,716 to $389,753 USD for US-based applicants. The position is also eligible for equity, with the final salary determined by factors such as location, travel, relevant prior experience, and specific skills.
What does the interview process focus on?
The interview process explores foundational skills and collaboration with AI. Candidates are evaluated on their ability to explain their approach, demonstrating not just what they know, but how they think.