Define the multi-year ML direction, modeling roadmap, and shared objectives and key results with partners while leading, mentoring, and growing a team of engineers.
Architect and optimize sub-second ML/Large Language Models (LLM) inference and agentic reasoning loops enabling real-time intent resolution, adaptive follow-up questioning, and moderation transparency.
Lead the transition from fragmented models to unified joint-modeling architectures.
Advocate scalable evaluation frameworks spanning structured facts and unstructured claims, active learning pipelines, and synthetic data generation to maximize model performance.
Cultivate engineering excellence across the organization.
Minimum qualifications
Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience with ML design and end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
Experience in a technical leadership role, managing a team of engineers.
Experience with Generative AI (e.g., Large Language Models (LLMs), diffusion models), development workflows, and use cases.
Preferred qualifications
Master's degree or PhD in Machine Learning, Artificial Intelligence, Computer Science, or a related quantitative field.
8 years of experience with data structures and algorithms.
Experience designing automated evaluation frameworks and experimentation for generative AI and ML systems.
Experience in one or more adjacent domains including Content Moderation, Conversational AI, Multimodal Fusion, or Truth Synthesis systems.
Experience in people management within cross-functional environments.
Ability to align and influence stakeholders across multiple engineering, product, and operations organizations.
Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience with ML design and end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
Experience in a technical leadership role, managing a team of engineers.
Experience with Generative AI (e.g., Large Language Models (LLMs), diffusion models), development workflows, and use cases.
