Machine Learning Engineer, Robinhood
GenAI
$157-185k
Plus equity
Commission-free stock trading & investing app
Job no longer available
Commission-free stock trading & investing app
1001+ employees
Job no longer available
$157-185k
Plus equity
1001+ employees
Company mission
To democratize finance for all.
Role
Who you are
- 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
- 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
What the job involves
- 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
- 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
- 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
Our take
For years, traditional brokers ruled the share trading realm, charging hefty fees that locked out everyday investors. Robinhood emerged as a disruptor, offering commission-free trading and opening the door to a new generation. Since then, expectations have continued to evolve, with investors looking not just to lower costs, but for simpler tools, clearer information, and guidance that makes the market easier to understand.
Robinhood was built to meet those changing expectations, designed from the start as a mobile-first platform that makes investor more accessible and less intimidating for people at every stage of their financial journey. Through its app, users can trade stocks and other financial instruments while benefiting from a clean interface and built-in educational support, helping them move from curiosity to confidence without unnecessary complexity.
Recently, Robinhood has strenghtned its impact too, particularly in the UK. With the launch of AI-powered Digests within its Robinhood Cortex assistant that helps users understand what's driving stock movements in plain English, while upcoming options trading and expanded educational resources add flexibility and depth. Together, these steps position Robinhood as a platform evolving alongside its users, blending technology and education to stay ahead in an ever-changing investment landscape.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 13 rounds)
Feb 2021
$2.4bn
CONVERTIBLE
Jan 2021
$1bn
LATE VC
Total funding: $5.6bn
Company HQ
Downtown Menlo Park, Menlo Park, CA
Leadership
Vlad Tenev
(Co-Founder, CEO & Chairman)Studied Mathematics at Stanford University, where they met Baiju. Dropped out of a PhD to start Robinhood. Alongside Robinhood, Vlad is also the co-founder and Executive Chairman of Harmonic.
Baiju B.
(Co-Founder)Studied Mathematics and Physics at Stanford University, where they met their Vlad and co-founded Robinhood in 2012. Baiju is also the Founder and CEO of Aetherflux.
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