Machine Learning Engineer, GenAi

About the team + role

We are seeking a dedicated and ambitious individual to accelerate the development and expansion of products powered by Gen AI to democratize finance at an unprecedented pace. In this role, you'll play a key part in Robinhood’s forward trajectory, collaborating closely with our adept Data Science and Engineering teams. The Gen AI team is devoted to bridging the transition of Gen AI & ML modeling work into production-grade applications. Robinhood operates at the intersection of data-driven insights and technological innovation.

The role is located in the office location(s) listed on this job description which will align with our in-office working environment. Please connect with your recruiter for more information regarding our in-office philosophy and expectations.

What you’ll do

In your role as a Machine Learning Engineer, you will focus on leveraging and optimizing Large Language Models (LLMs) along with the implementation of advanced AI technologies. Your key responsibilities will include:

1. Development and Optimization of LLMs: Implement and fine-tune state-of-the-art Large Language Models for various applications, focusing on performance and accuracy.
2. Evaluating Model Performance: Conduct rigorous evaluations of LLMs, assessing effectiveness, efficiency, and business alignment.
3. Integration of Advanced AI Technologies: Implement Retrieval-Augmented Generation (RAG), function calling, and code interpreter technologies to enhance the capabilities of Large Language Models.
4. Research and Development: Stay abreast of the latest advancements in machine learning, particularly in LLMs, LLM agents, and large-scale neural network training.
5. Data and Model Parallel Training: Utilize data and model parallel training techniques for efficient handling of large-scale models.
6. GPU Cluster Management for Training: Oversee extensive training jobs on GPU clusters, ensuring optimal resource utilization for complex tasks.
7. Cross-Functional Collaboration and Leadership: Work with ML engineers, data scientists, and product teams, providing guidance and mentorship.
8. Documentation and Reporting: Maintain detailed documentation of methodologies, models, and results, and communicate findings across the organization.

What you bring

1. Advanced Degree: Master's or PhD in Computer Science, AI, Linguistics, or related fields, with a focus on machine learning and natural language processing.
2. Experience with LLMs and PyTorch: Extensive experience with large language models and proficiency in PyTorch.
3. Expertise in Parallel Training and GPU Cluster Management: Strong background in parallel training methods and managing large-scale training jobs on GPU clusters.
4. Analytical and Problem-Solving Skills: Ability to address complex challenges in model training and optimization.
5. Leadership and Mentorship Capabilities: Proven leadership in guiding projects and mentoring team members.
6. Communication and Collaboration Skills: Effective communication skills for conveying technical concepts and collaborating with cross-functional teams.
7. Innovation and Continuous Learning: Passion for staying updated with the latest trends in AI and machine learning.

What we offer

• Market competitive and pay equity-focused compensation structure
• 100% paid health insurance for employees with 90% coverage for dependents
• Annual lifestyle wallet for personal wellness, learning and development, and more!
• Lifetime maximum benefit for family forming and fertility benefits
• Dedicated mental health support for employees and eligible dependents
• Generous time away including company holidays, paid time off, sick time, parental leave, and more!
• Lively office environment with catered meals, fully stocked kitchens, and geo-specific commuter benefits

Last updated on Aug 22, 2024