AI Research Intern

DRW -posted 6 months ago
$175,000 - $200,000/Yr
Intern
Palo Alto, CA
1,001-5,000 employees
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As an AI Research Intern, you will be an integral member of a team of experienced technologists, quantitative researchers, and traders. You will collaborate closely with other researchers to solve challenging AI and machine learning problems. Your projects will vary depending on priorities at the start of your employment and could include solving forecasting problems or developing large language models (LLMs). We are looking for individuals eager to learn new AI technologies, create innovative solutions, and choose the right tools to directly impact our business. You will be surrounded by cutting-edge technology, given immediate responsibility, mentored by industry-leading experts, and attend a robust training program to ensure your success at DRW.

  • Creating and testing new AI models and algorithms to solve specific problems or improve existing methods.
  • Building data pipelines for model training and evaluation, including data collection, cleaning, preprocessing, and labeling.
  • Designing and implementing rigorous testing frameworks to assess model performance and identify areas for improvement.
  • Working closely with team members to establish and refine research methodologies, promoting peer reviews, testing, and thorough documentation.
  • Staying updated on the latest AI techniques and advancements, sharing insights, and actively bringing improvements to research processes.
  • Pursuing a PhD in artificial intelligence, machine learning, computer science, or a related field graduating between December 2026 and June 2027.
  • Strong foundation in AI concepts.
  • Strong knowledge of machine learning.
  • Solid technical and programming skills (Python, Java, GitHub).
  • Familiarity with machine learning framework (Spark, PyTorch, etc.).
  • Excellent analytical, problem-solving, and communication skills.
  • Deep interest in financial markets.
  • Experience with NLP tasks.
  • Knowledge of TensorFlow or PyTorch.
  • Basic understanding of MLOps principles (monitoring, versioning, model serving).
  • Gain in-depth experience with cutting-edge ML/AI techniques and model deployment.
  • Develop robust machine learning research skills, from data engineering to model evaluation.
  • Contribute to research projects with potential impact on financial decision-making and other applied domains.
  • Engage in fostering a collaborative research culture, driving improvements in research quality, and interdisciplinary collaboration.
  • Community activities including educational, social and team-building events.
  • Housing provided with fully furnished apartments close to the office.
  • Mentorship from experienced professionals in the field.
  • Educational courses on options trading and technology immersion.
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