Top Tech Jobs & Startup Jobs

Own and implement iOS ad functionality across the app and publisher SDK: ad rendering, viewability, client-side mediation, SDK integrations, production health, and experiment-driven measurement to ensure accurate impressions, clicks, billing, and stable app behavior.

Lead product for the core NewsBreak app experience: define goals, write PRDs, drive cross-team delivery for the For You feed, prioritize experience issues by predicted churn impact, scale validated directions, and manage one PM to close the loop on high-priority issues.

Lead design and execution of geo holdouts and incrementality tests, build DMA-level LTV models and geo-tiered bidding, define objective functions and decision rules for automated bidding, set experiment power and success criteria, and support paid and organic growth teams.

Lead product efforts to discover and validate new AI-native product directions for local content. Formulate falsifiable hypotheses, run rapid experiments, analyze results, kill or validate directions, and hand validated concepts to Senior PMs to scale.

Lead and operate paid growth: design rigorous incrementality experiments, standardize testing, control agentic bidding rollout, implement geo-tiered bidding, reallocate cross-channel budgets, extract platform support, and rebalance the growth team for efficiency.

Lead full-cycle partnerships to acquire local/home-services advertising budgets at scale. Source, pitch, negotiate, onboard one-to-many partners, collaborate cross-functionally, and report on pipeline, deals, and local ad spend metrics.

Build and maintain backend and data pipelines powering ads, personalization, and retention systems. Contribute to recommendation algorithms, feature pipelines, experimentation infrastructure, revenue operations tooling (commission/quota), and observability for large-scale user and engagement data. Collaborate with product, sales, and finance to ship reliable, low-latency production systems and monitoring.

Build and maintain ML infrastructure for training, serving, and monitoring models for Ads and Recommendations. Improve training reliability and serving performance, own core ML infra components (pipelines, feature/embedding platform), address production issues, and collaborate with ML engineers to deliver robust model pipelines.

Lead post-training for LLMs (CPT, SFT, RL) focusing on RL methods; design and curate training and reward data; run and debug distributed training on mid-to-large GPU clusters; build evaluation and verifier pipelines; partner with product and business teams to deliver targeted model improvements quickly.