AI Model Lead

Danaher•Austin, TX

About The Position

The AI Model Lead is the senior technical owner responsible for architecting and delivering advanced AI models that power mission‑critical products. This role requires deep ML expertise, strong architectural judgment, and the ability to influence strategy across multiple teams. You will lead high‑impact initiatives, mentor senior engineers, and drive innovation in model development, optimization, and deployment. In this role, you will have the opportunity to: Own the end‑to‑end architecture and technical strategy for large‑scale AI/ML models, including LLMs and multimodal systems. Lead development, training, and optimization of advanced models using state‑of‑the‑art deep learning and distributed training techniques. Drive cross‑org alignment by partnering with product, research, infra, and engineering leaders to shape long‑term AI roadmap and priorities. Mentor and elevate senior ML engineers and researchers, setting technical standards and guiding complex design decisions. Ensure operational excellence through scalable MLOps pipelines, rigorous evaluation frameworks, and responsible AI practices.

Requirements

Bachelor’s degree in data science, Engineering, Information Systems, or equivalent experience and 12+ years of experience in ML, deep learning, or applied AI.
Expert‑level proficiency in PyTorch, TensorFlow, JAX, or similar frameworks.
Deep understanding of distributed training, model parallelism, and large‑scale data pipelines.
Strong ability to influence technical direction across teams and orgs.
Demonstrated experience mentoring senior engineers or researchers.

Nice To Haves

Experience building or fine‑tuning LLMs, multimodal models, or foundation models.
Publications in top AI/ML conferences (NeurIPS, ICML, ICLR, CVPR, ACL).
Experience with cloud‑scale ML infrastructure (Azure, AWS, GCP).
Background in model safety, responsible AI, or evaluation frameworks.

Responsibilities

Own the end‑to‑end architecture and technical strategy for large‑scale AI/ML models, including LLMs and multimodal systems.
Lead development, training, and optimization of advanced models using state‑of‑the‑art deep learning and distributed training techniques.
Drive cross‑org alignment by partnering with product, research, infra, and engineering leaders to shape long‑term AI roadmap and priorities.
Mentor and elevate senior ML engineers and researchers, setting technical standards and guiding complex design decisions.
Ensure operational excellence through scalable MLOps pipelines, rigorous evaluation frameworks, and responsible AI practices.