Machine Learning Engineer

Robinhood Robinhood · Fintech · [ProspectLand] · [Prospect]

Robinhood is seeking a Machine Learning Engineer to join their AI Research and Development team. The role focuses on implementing and evaluating ML algorithms, developing scalable models for ranking and recommendation systems, and applying techniques like collaborative filtering, content-based filtering, hybrid models, Learning to Rank (LTR), reinforcement learning, and multi-armed bandits. The engineer will also design and conduct A/B tests, analyze experimental data, collaborate with cross-functional teams, and build reusable ML libraries.

What you'd actually do

  1. AI and ML Research: Evaluate cutting technologies, including but not limited to, transformer-based model architecture and large foundational models to identify solutions for Robinhood specific problems.
  2. Model Development and Implementation: Develop and implement scalable machine learning models focusing on advanced ranking and recommendation systems, including expertise in Collaborative Filtering, Content Based Filtering, and Hybrid models, alongside proficiency in Learning to Rank (LTR) techniques for effective prioritization. Additionally, design reinforcement learning algorithms and apply multi-armed bandits strategies to optimize decision-making in dynamic environments, balancing exploration and exploitation.
  3. A/B Testing and Experimentation: Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance, and analyzing results.
  4. Data Analysis and Insight Generation: Analyze experimental data to extract actionable insights. Use statistical techniques to validate the findings and ensure their relevance and accuracy.
  5. Cross-Functional Collaboration: Work closely with other engineering teams, data scientists, and the marketing team to integrate machine learning models into the product and ensure they meet business requirements. Present results to different stakeholders.

Skills

Required

  • Bachelor’s degree or foreign equivalent in Computer Science or related field and three years (3) of experience in job offered or related occupation. Alternatively, a Masters in Computer Science or related field and one year (1) of experience in job offered or related occupation
  • Machine learning algorithms
  • Transformer-based model architecture
  • Large foundational models
  • Ranking and recommendation systems
  • Collaborative Filtering
  • Content Based Filtering
  • Hybrid models
  • Learning to Rank (LTR)
  • Reinforcement learning
  • Multi-armed bandit strategies
  • A/B Testing
  • Data Analysis
  • Statistical techniques

Nice to have

  • Build reusable libraries for common machine learning practices
  • Offer support and guidance to the usage of these tools
  • Maintain comprehensive documentation

What the JD emphasized

  • advanced ranking and recommendation systems
  • reinforcement learning algorithms
  • multi-armed bandit strategies

Other signals

  • applying frontier technologies
  • implement and evaluate machine learning algorithms
  • develop and implement scalable machine learning models
  • design and conduct A/B tests
  • analyze experimental data