Staff , Machine-Learning
1 day ago
What You’ll Do
- Lead the development of cutting-edge machine learning algorithms in organization’s predictive search/type-ahead, content recommendations, or algorithmic customer understanding teams.
- Continually improve teams’ ability to build efficient machine learning models by leveraging industry best practices and set high standards for craftsmanship of the entire team.
- Mentor a team of machine learning engineers, continuously upskill them while modeling a culture of continuous research and innovation.
- Collaborate closely with the product and engineering leaders in our SMART technologies group to build a next-generation search and recommendations stack and the organization required to maintain and innovate on it
- Contribute as a senior leader beyond the SMART group, in particular within organization’s broader ML community
- Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on.
What You’ll Need
- Bachelor's or Master’s degree in Computer Science, Mathematics, Statics or a related field.
- 10+ years of experience in building large scale machine learning algorithms
- 4+ years in an architect or technical leadership position
- Strong theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, transformers and NLP techniques.
- Proficiency in programming languages such as Python or R and relevant ML libraries (e.g., TensorFlow, PyTorch) to develop production-grade quality product
- Ability to partner cross-functionally to own and shape technical roadmaps
- Intellectual curiosity and a desire to always be learning
Nice to have
- PhD in Computer Science, Mathematics, Statistics or related field
- Familiarity with suggest/type-ahead systems, search and ranking, or content recommendations
- Familiarity with Generative AI and their usage in improving search and recommender systems.
- Familiarity with GCP (or AWS, Azure), ML model development frameworks, ML orchestration tools (Airflow, Kubeflow or MLFlow)
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