Summary

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

1. Market competitive and pay equity-focused compensation structure
2. 100% paid health insurance for employees with 90% coverage for dependents
3. Annual lifestyle wallet for personal wellness, learning and development, and more!
4. Lifetime maximum benefit for family forming and fertility benefits
5. Dedicated mental health support for employees and eligible dependents
6. Generous time away including company holidays, paid time off, sick time, parental leave, and more!
7. Lively office environment with catered meals, fully stocked kitchens, and geo-specific commuter benefits

Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected salary range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. This role is also eligible to participate in a Robinhood bonus plan and Robinhood’s equity plan. For other locations not listed, compensation can be discussed with your recruiter during the interview process.

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)

$157,000—$185,000 USD

Zone 2 (Denver, CO; Westlake, TX; Chicago, IL)

$139,000—$163,000 USD

Zone 3 (Lake Mary, FL)

$122,000—$144,000 USD

Skills

• Analytical Thinking
• Communications Skills
• Development
• Generative AI
• Machine Learning
• Problem Solving
• Team Collaboration