Machine Learning Engineer, GenAI

at  Robinhood

JOIN A LEADING FINTECH COMPANY THAT’S DEMOCRATIZING FINANCE FOR ALL.

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 you’re invigorated by our mission, values, and drive to change the world — we’d love to have you apply.

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
  Click here to learn more about available Benefits, which vary by region and Robinhood entity.
  We’re looking for more growth-minded and collaborative people to be a part of our journey in democratizing finance for all. If you’re ready to give 100% in helping us achieve our mission—we’d love to have you apply even if you feel unsure about whether you meet every single requirement in this posting. At Robinhood, we’re looking for people invigorated by our mission, values, and drive to change the world, not just those who simply check off all the boxes.
  Robinhood embraces a diversity of backgrounds and experiences and provides equal opportunity for all applicants and employees. We are dedicated to building a company that represents a variety of backgrounds, perspectives, and skills. We believe that the more inclusive we are, the better our work (and work environment) will be for everyone. Additionally, Robinhood provides reasonable accommodations for candidates on request and respects applicants’ privacy rights. Please review the specific Robinhood Privacy Policy applicable to the country where you are applying

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:

• 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.