Senior Machine Learning Engineer
Generative AI
Updated on 2/21/2024
Robinhood

1,001-5,000 employees

Accessible, affordable trading and investment platform.
Company Overview
Robinhood is a pioneering financial services company that democratizes finance by offering accessible and affordable trading services to all, regardless of wealth or industry knowledge. The company's competitive advantage lies in its intuitive platform, which simplifies trading and investing in stocks, options, and cryptocurrencies, and its commitment to inclusivity, which breaks down traditional barriers in the financial industry. As an industry leader, Robinhood is recognized for its technical innovation, including its proprietary clearing system, and its commitment to transparency and customer empowerment.
Fintech

Company Stage

N/A

Total Funding

$7.4B

Founded

2013

Headquarters

West Menlo Park, California

Growth & Insights
Headcount

6 month growth

0%

1 year growth

3%

2 year growth

-21%
Locations
Menlo Park, CA, USA • New York, NY, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Pytorch
CategoriesNew
AI & Machine Learning
Requirements
  • Master's or PhD in Computer Science, AI, Linguistics, or related fields
  • Extensive experience with large language models and proficiency in PyTorch
  • Strong background in parallel training methods and managing large-scale training jobs on GPU clusters
  • Ability to address complex challenges in model training and optimization
  • Proven leadership in guiding projects and mentoring team members
  • Effective communication skills for conveying technical concepts and collaborating with cross-functional teams
  • Passion for staying updated with the latest trends in AI and machine learning
Responsibilities
  • Implement and fine-tune state-of-the-art Large Language Models for various applications, focusing on performance and accuracy
  • Conduct rigorous evaluations of LLMs, assessing effectiveness, efficiency, and business alignment
  • Implement Retrieval-Augmented Generation (RAG), function calling, and code interpreter technologies to enhance the capabilities of Large Language Models
  • Stay abreast of the latest advancements in machine learning, particularly in LLMs, LLM agents, and large-scale neural network training
  • Utilize data and model parallel training techniques for efficient handling of large-scale models
  • Oversee extensive training jobs on GPU clusters, ensuring optimal resource utilization for complex tasks
  • Work with ML engineers, data scientists, and product teams, providing guidance and mentorship
  • Maintain detailed documentation of methodologies, models, and results, and communicate findings across the organization
Desired Qualifications
  • Passion for staying updated with the latest trends in AI and machine learning