Senior Machine Learning Engineer Job at Robinhood (Menlo Park)

Senior Machine Learning Engineer

Robinhood

Location:
United States , Menlo Park ▼
Bellevue

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

187000.00 - 220000.00 USD / Year

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Job Description:

Join us in building the future of finance. Our mission is to democratize finance for all. The mission of the AI Research and Development team is to provide scalable data and model driven decision making solutions to the various business functions at Robinhood. We aim to create a personalized experience for our users, by helping them discover & engage with the right products & features within Robinhood that they might find most valuable. To accelerate progress, we are also building an accessible model development platform to democratize machine learning practices throughout the company.

Job Responsibility:

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
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 bandit strategies to optimize decision-making in dynamic environments, balancing exploration and exploitation
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
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
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
Tooling and Documentation: Build reusable libraries for common machine learning practices. Offer support and guidance to the usage of these tools. Maintain comprehensive documentation of libraries, models, experiments, and findings

Requirements:

5+ years of applied ML experience productionizing ML models with 2+ years focused on recommendations, ranking or personalization projects
A fervent interest in exploring and applying AI and ML technologies
Strive to solve sophisticated engineering problems that drive business objectives
Solid technical foundation enabling active contribution to the design and execution of projects and ideas
Familiarity with architectural frameworks of large, distributed, and high-scale ML applications
Hands-on experience in classical ML techniques with tabular data as well as modern techniques with sequential data
Proven experience in ML with a focus on ranking, recommendation systems, multi-objective optimization, and reinforcement learning
Proficiency in Python, SQL, XGboost, PyTorch/TensorFlow

Nice to have:

Experience with Spark, Kafka, and Kubernetes is also desirable
Ideally you have experience in the Finance sector

What we offer:

Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
100% paid health insurance for employees with 90% coverage for dependents
Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
Employer-paid life & disability insurance, fertility benefits, and mental health benefits
Time off to recharge including company holidays, paid time off, sick time, parental leave, and more
Exceptional office experience with catered meals, events, and comfortable workspaces

Additional Information:

Job Posted:
January 06, 2026

Employment Type:

Fulltime

Work Type:

On-site work

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