Overview
Staff Applied Scientist - I is a Data Science role focused on classical machine learning, large-scale recommendation systems, and agentic/autonomous AI systems for personalization.
What you'll do
- Design, build, and deploy large-scale recommendation systems using advanced ML and deep learning.
- Own the end-to-end ML lifecycle including data preparation, training, evaluation, and deployment pipelines.
- Run rapid experimentation workflows to validate hypotheses and measure business impact.
- Monitor model performance and identify drifts, failure modes, and improvement opportunities.
- Build agentic AI systems to automate tasks like observing model performance, triggering experiments, and tuning hyperparameters.
- Use LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models for semantic and preference modeling.
What you'll need
- 6+ years of industry experience in ML/Data Science, ideally in large-scale recommendation systems or personalization.
- Experience deploying ML workflows/models in production systems.
- Experience building end-to-end ML solutions from prototype to production.
- Proficiency in Python and statistical tools (e.g., R, NumPy, SciPy, PyTorch/TensorFlow).
- Expertise with algorithms in areas including NLP, Reinforcement Learning, Time Series, and Deep Learning on real-world datasets.
- Big data and cloud experience (e.g., Spark and cloud platforms such as Azure/AWS/GCP/Vertex AI).
Details
Read the full description and apply on the company’s own careers page.
