Top Tech Jobs & Startup Jobs

Design and deploy next-generation recommendation and ranking models using LLMs, RLHF, and preference learning. Build user-understanding systems, apply RL and optimization to bidding and ad delivery, run causal A/B experiments, and collaborate with engineering to productionize research across the ML pipeline.

Design and evaluate next-generation recommendation and ranking models using LLMs, RLHF, and preference learning. Build user understanding systems for conversion and value estimation at scale. Apply RL and optimization to bidding and real-time delivery. Run causal inference, A/B tests, and offline evaluations. Collaborate with engineering to productionize research and communicate results to technical and non-technical stakeholders.

Design, build, and evaluate next-generation ranking and recommendation models using LLMs, RLHF, and preference learning. Develop user understanding systems for conversion and value estimation at massive scale. Apply reinforcement learning and optimization to bidding and auction dynamics. Design and run causal inference and A/B experiments. Partner with engineering to productionize models and communicate results to technical and non-technical stakeholders.

The role involves developing cross-platform API abstractions for the Unity Editor using modern C++. Responsibilities include maintaining codebases and collaborating with worldwide teams.

The Lead Compensation Program Manager strategizes Unity's market positioning, manages global salary structures, drives job architecture redesign, and integrates AI tools for compensation processes.

Lead the development and implementation of global compensation strategies, integrating AI tools to enhance efficiency in salary structures and job architecture.

Lead the design of global compensation strategies, benchmark salaries, implement job architecture, and innovate compensation processes using AI tools.

Lead the development and management of global compensation strategies, structures, and processes while integrating AI tools and partnering with leadership and recruiting teams.

The role involves designing large-scale data pipelines for machine learning, improving ML workflows, and ensuring efficiency in distributed model training environments. Key responsibilities include developing infrastructure, integrating ML pipelines, optimizing performance, and collaborating with ML engineers on large-scale experimentation.

Design and operate large-scale ML data pipelines, develop infrastructure for distributed training workflows, and ensure reliability and performance of the offline ML platform.