Basic Qualifications:
* Currently pursuing a B.S., M.S., or Ph.D. in Computer Science, Statistics, or a related field.
* Solid ML/DL fundamentals and the ability to explain model and method choices.
* Hands-on experience training and evaluating deep learning models (for example, with PyTorch) or building and evaluating LLM-based systems.
* Experience with recommender systems, user representation learning, NLP, multimodal learning, LLMs, or AI agents.
* Experience reading research papers and reproducing results.
* Clear written and spoken English communication; ability to work independently and with a team.
* Responsible use of AI coding assistants: able to verify, debug, and explain the code produced.
Preferred Qualifications:
* Experience with recommender systems, user representation learning, NLP, multimodal learning, LLMs, or AI agents.
* Familiarity with experiment tracking and evaluation tools such as MLflow or Weights & Biases.
* SQL and large-scale data processing experience, such as Spark; publications, competition results, or open-source contributions are a plus.
* Communicates with data and metrics, translating technical trade-offs into costs, risks, and benefits that business and operations stakeholders can understand.
* Favors high-leverage ways of working: automation, reusable capabilities, clear documentation, and sound engineering practices.
* Currently pursuing a B.S., M.S., or Ph.D. in Computer Science, Statistics, or a related field.
* Solid ML/DL fundamentals and the ability to explain model and method choices.
* Hands-on experience training and evaluating deep learning models (for example, with PyTorch) or building and evaluating LLM-based systems.
* Experience with recommender systems, user representation learning, NLP, multimodal learning, LLMs, or AI agents.
* Experience reading research papers and reproducing results.
* Clear written and spoken English communication; ability to work independently and with a team.
* Responsible use of AI coding assistants: able to verify, debug, and explain the code produced.
Preferred Qualifications:
* Experience with recommender systems, user representation learning, NLP, multimodal learning, LLMs, or AI agents.
* Familiarity with experiment tracking and evaluation tools such as MLflow or Weights & Biases.
* SQL and large-scale data processing experience, such as Spark; publications, competition results, or open-source contributions are a plus.
* Communicates with data and metrics, translating technical trade-offs into costs, risks, and benefits that business and operations stakeholders can understand.
* Favors high-leverage ways of working: automation, reusable capabilities, clear documentation, and sound engineering practices.