Applied Scientist, Rbs Tech

Amazon Amazon · Big Tech · IN, KA, Bengaluru · Applied Science

Applied Scientist role focused on foundational ML research and developing scalable GenAI, NLP, and Computer Vision solutions for customer experience and operations automation. The role involves designing and deploying models for multi-modal understanding, task automation with LLM agents, and improving product data quality through techniques like similarity retrieval and anomaly detection. It emphasizes research, experimentation, and potential patent/publication opportunities.

What you'd actually do

  1. design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues.
  2. develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems.
  3. define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time.
  4. partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation.
  5. independently file for patents and/or publish research work where opportunities arise.

Skills

Required

  • Masters’ degree in Electrical Engineering, Computer Science, Computer Engineering, Mathematics, or related field with specialization in machine learning, NLP, Computer Vision, deep or related fields.
  • 2+ years of relevant applied science research experience

Nice to have

  • publications at top-tier peer-reviewed conferences or journals
  • written and verbal communication skills to communicate with technical and non-technical audiences, including senior leadership
  • Knowledge of deep learning, machine learning and statistics
  • Knowledge of computer science fundamentals in data structures, algorithm design, and problem solving
  • Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.

What the JD emphasized

  • foundational ML research
  • scalable state-of-the-art ML solutions
  • multi-modal understanding (text and images)
  • task automation through multi-modal LLM Agents
  • novel LLM, deep learning and statistical techniques
  • scientific innovation
  • publish research work

Other signals

  • GenAI platforms for automation
  • multi-modal understanding (text and images)
  • task automation through multi-modal LLM Agents
  • supervised and unsupervised techniques
  • multi-task learning
  • multi-label classification
  • aspect and topic extraction
  • image and text similarity and retrieval
  • product groupings
  • identifying duplicate listings
  • design and deploy scalable GenAI, NLP and Computer Vision solutions
  • develop novel LLM, deep learning and statistical techniques
  • task automation, text processing, image processing, pattern recognition, and anomaly detection problems
  • define the research and experiments strategy
  • develop AI/ML models and progressively improve the results over time
  • partner with business and engineering teams
  • solve large and significantly complex problems that require scientific innovation
  • independently file for patents and/or publish research work
  • impact the large product strategy
  • identifies new business opportunities
  • provides strategic direction