Staff , Machine-Learning

7 days ago


Bangalore, India Wenger & Watson Full time

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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