Staff Applied Scientist

What you'll do

• Lead complex ML initiatives from design through production, including model training and serving, lifecycle management, and customer-specific model pipelines.
• Set technical vision and quality standards for the product portfolio and ML platform; review designs and code, and mentor senior engineers and data scientists.
• Coordinate cross-team initiatives and connect technical decisions to customer and business outcomes.

What they ask for

• 8+ years building production ML systems, with hands-on experience across data science, ML engineering, and ML operations.
• Experience designing and training models and building and operating production pipelines and services.
• Deep experience deploying predictive models, including supervised and unsupervised learning, neural networks, or recommenders, using frameworks such as PyTorch and Tensorflow.
• Strong distributed systems fundamentals and experience designing for scale, reliability, and cost.

Nice to have

• Production experience with recommender systems, multi-armed bandits, or uplift modeling; or ML platform tooling such as MLflow, Ray, feature stores, or ML observability.
• Experience with Python, Ruby on Rails, MongoDB, Redis, or Kubernetes; or in customer engagement, personalization, or marketing technology.

Pay

USD 184,000 to USD 299,812/year (base salary); USD 204,000 to USD 332,400/year (On Target Earnings, including bonus or commission)

Tools

PyTorch, Tensorflow, MLflow, Ray, Python, Ruby on Rails, MongoDB, Redis

AI focus

Build and operate predictive and generative AI-enhanced marketing solutions, including customer-specific models, training pipelines, and high-throughput prediction APIs.