Staff Applied AI Engineer

What you'll do

• Design and lead ML pipelines, training infrastructure, model-serving systems, and data foundations.
• Build evaluation systems and train, fine-tune, deploy, and maintain generative models in production.
• Set technical direction, establish engineering standards, and mentor team members.

What they ask for

• Strong track record architecting and shipping production ML systems, with systems-level experience scaling ML output and quality.
• Proficiency in Python and Linux, hands-on experience with PyTorch and/or TensorFlow, and strong machine-learning fundamentals.
• Experience training, fine-tuning, and evaluating models on large-scale datasets, and deploying and maintaining AI models in cloud production environments at scale.
• Bachelor's or Master's (or equivalent experience) in Computer Science, Mathematics, AI/ML, or a related field.

Nice to have

• Production experience with text-to-image or diffusion systems.
• Experience building ML platforms or infrastructure at scale, or a track record of technical leadership.

Tools

Python, Linux, PyTorch, TensorFlow, diffusion models, LLMs

AI focus

Build and scale generative AI systems, including diffusion and text-to-image models and LLM applications; train, fine-tune, evaluate, deploy, and improve models and pipelines.