Role overview
Robinhood Markets was founded on a simple idea: that our financial markets should be accessible to all. With customers at the heart of our decisions, Robinhood and its subsidiaries and affiliates are lowering barriers and providing greater access to financial information. Together, we are building products and services that help create a financial system everyone can participate in.
With growth as the top priority...
The business is seeking curious, growth-minded thinkers to help shape our vision, structures and systems; playing a key-role as we launch into our ambitious future. If youâre invigorated by our mission, values, and drive to change the world â weâd love to have you apply.
What you'll work on
- Development and Optimization of LLMs: Implement and fine-tune state-of-the-art Large Language Models for various applications, focusing on performance and accuracy.
- Evaluating Model Performance: Conduct rigorous evaluations of LLMs, assessing effectiveness, efficiency, and business alignment.
- Integration of Advanced AI Technologies: Implement Retrieval-Augmented Generation (RAG), function calling, and code interpreter technologies to enhance the capabilities of Large Language Models.
- Research and Development: Stay abreast of the latest advancements in machine learning, particularly in LLMs, LLM agents, and large-scale neural network training.
- Data and Model Parallel Training: Utilize data and model parallel training techniques for efficient handling of large-scale models.
- GPU Cluster Management for Training: Oversee extensive training jobs on GPU clusters, ensuring optimal resource utilization for complex tasks.
- Cross-Functional Collaboration and Leadership: Work with ML engineers, data scientists, and product teams, providing guidance and mentorship.
- Documentation and Reporting: Maintain detailed documentation of methodologies, models, and results, and communicate findings across the organization.
What we're looking for
- Advanced Degree: Master's or PhD in Computer Science, AI, Linguistics, or related fields, with a focus on machine learning and natural language processing.
- Experience with LLMs and PyTorch: Extensive experience with large language models and proficiency in PyTorch.
- Expertise in Parallel Training and GPU Cluster Management: Strong background in parallel training methods and managing large-scale training jobs on GPU clusters.
- Analytical and Problem-Solving Skills: Ability to address complex challenges in model training and optimization.
- Leadership and Mentorship Capabilities: Proven leadership in guiding projects and mentoring team members.
- Communication and Collaboration Skills: Effective communication skills for conveying technical concepts and collaborating with cross-functional teams.
- Innovation and Continuous Learning: Passion for staying updated with the latest trends in AI and machine learning.
Tags & focus areas
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