Top Tech Jobs & Startup Jobs

Set technical vision for Pinterest’s Product ML Infrastructure, leading distributed model training, fine-tuning, evaluation, and high-scale CPU/GPU inference. Improve GPU efficiency, data loading, execution, kernels, memory, compilation, quantization, scheduling, and capacity. Build reliable, observable training and serving platforms, drive architecture decisions and migrations, partner with AI/ML teams, mentor senior engineers, and establish operational standards across the organization.

Leads Pinterest’s advertiser measurement and signal-quality engineering organization, defining multi-year strategy across machine learning, data platforms, experimentation, privacy, and reliability. Manages managers and senior technical leaders, partners with product and cross-functional teams, drives scalable solutions for advertiser challenges, improves model quality and data integrity, establishes governance mechanisms, communicates with executives, and builds an inclusive high-performing organization.

Leads and grows engineering teams building scalable machine learning, backend, and data platforms for advertising measurement. Sets technical strategy, productionizes causal inference and experimentation solutions, and develops products such as incrementality, lift testing, attribution, anomaly detection, and automated insights. Partners across Product, Data Science, Ads Engineering, Infrastructure, and Sales while hiring and mentoring technical leaders. Champions AI-assisted development with strong standards for validation, explainability, privacy, governance, and accountability.

Design and develop machine learning algorithms for target ROAS, automatic bidding, and ads pacing. Explore bid landscapes, optimize advertiser value and revenue, conduct A/B experiments, and collaborate with product, sales, and engineering teams on new ad products and bidding strategies. Provide staff-level technical leadership, drive cross-team alignment, and use AI-assisted development and productivity tools to improve engineering workflows.

Leads the technical vision and execution of Pinterest’s large-scale indexing and retrieval infrastructure across Core, Ads, and Shopping. Drives architecture modernization, real-time and incremental retrieval, shared platform capabilities, metrics, debugging workflows, and improvements in relevance, freshness, reliability, coverage, and cost. Partners across engineering, product, ML, and infrastructure organizations, mentors senior technical staff, and validates AI-assisted engineering work with strong attention to correctness, privacy, safety, and operational excellence.

Leads an analytics engineering team supporting Core Data Science by building reliable data foundations, tooling, analysis pipelines, and self-service datasets. Establishes instrumentation, experimentation, documentation, data quality, and democratization practices. Partners with data scientists, engineers, product managers, designers, and researchers to turn insights into product impact. Requires expertise in large-scale data manipulation, SQL, Python or R, ETL/ELT, workflow orchestration, and AI-assisted analysis, along with engineering management experience.

Lead and mentor analytics engineers while building scalable data foundations, instrumentation, experimentation practices, AI-assisted analysis tools, ETL/ELT pipelines, and self-service datasets. Partner with data scientists, engineers, product managers, designers, and researchers to improve data quality, documentation, metric investigations, and insight-driven decision-making. Drive analytics engineering strategy, workflow optimization, and responsible use of AI across analysis and development processes.

Lead design and implementation of Pinterest Edge systems (CDN, TLS, DNS, proxies) to manage automation traffic and rate limiting at scale. Develop request-processing logic in Envoy, collaborate with vendors and platform teams, mentor engineers, use AI to accelerate workflows, and participate in on-call incident response and reliability improvements.

Leads Pinterest’s Capacity Engineering team and strategy across cloud capacity forecasting, supply planning, compute and GPU efficiency, infrastructure data, governance, and capacity operations. The role manages resource allocation systems, improves Kubernetes and cloud utilization, establishes cost and reliability metrics, partners with Infrastructure, SRE, Finance, product teams, and cloud providers, and develops senior technical talent. It also applies and verifies AI-assisted workflows for forecasting, analysis, and operational investigations.

Lead design and implementation of Pinterest's exabyte-scale data lake storage and metadata systems. Drive architecture and execution for scalable storage features supporting large ML/AI workloads, collaborate across data/ML/infrastructure teams, and contribute to open-source projects (Iceberg, Spark, Flink).