Machine Learning Engineer, AI Innovator
4 days ago
We are seeking a highly skilled Machine Learning Engineer to join our team at Robinhood, a leading fintech company dedicated to democratizing finance for all. As a key member of our Gen AI team, you will play a crucial role in accelerating the development and expansion of products powered by Gen AI.
Key Responsibilities- LLM Development and Optimization: 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.
- 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.
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