Staff Applied Scientist

What you'll do

• Identify and drive transformative initiatives to replatform model training, serving, and production infrastructure.
• Build and ship complex ML systems including distributed training, model lifecycle management, and high-throughput APIs.
• Own the team's technical vision, define best practices, and set the quality bar for the ML platform.
• Lead cross-team technical relationships to integrate solutions into messaging, analytics, and data platform surfaces.
• Raise engineering quality through design reviews, code reviews, and production readiness for ML systems.
• Mentor senior engineers and data scientists while maintaining a high personal output of technical delivery.
• Connect technical decisions to business outcomes and represent the team's perspective to leadership.

What we're looking for

• Must have 8+ years of experience building ML systems in production with depth in data science, ML engineering, and ML operations.
• Must have experience designing, training, and operating models and pipelines under production load.
• Must be a technical leader capable of owning team direction, leading multi-quarter initiatives, and mentoring senior engineers.
• Must have deep experience prototyping and deploying predictive models using frameworks such as PyTorch and Tensorflow.
• Must possess strong distributed systems fundamentals for designing at scale, reliability, and cost.
• Must be an effective verbal and written communicator capable of building consensus and driving decision making.
• Experience with recommender systems, multi-armed bandits, or uplift modeling in production (preferred).
• Experience with ML platform tooling, Python, Ruby on Rails, MongoDB, Redis, Kubernetes, or marketing technology domains (preferred).