Staff Applied Scientist

What you'll do

• Lead complex ML initiatives from design and prototype through production, including training and serving infrastructure and model lifecycle pipelines.
• Set technical vision and quality standards for the team’s product portfolio and ML platform; review designs and code, and mentor senior engineers and data scientists.
• Lead cross-team technical initiatives and connect engineering 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 prototyping, refining, and deploying predictive models using frameworks such as PyTorch and Tensorflow.
• Strong distributed systems fundamentals, including designing for scale, reliability, and cost.
• Technical leadership experience owning team direction, leading multi-quarter cross-team initiatives, and developing senior engineers.

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 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

Builds predictive and generative AI and ML solutions for personalized customer engagement, including customer-specific models, training pipelines, and high-throughput prediction APIs.