Senior Machine Learning Engineer, Applied ML

Posted 24 Days Ago
Be an Early Applicant
Menlo Park, CA
187K-220K Annually
Senior level
Fintech • Cryptocurrency
Robinhood's mission is to democratize finance for all.
The Role
The Senior Machine Learning Engineer will develop and implement scalable machine learning models, focusing on ranking and recommendation systems. Responsibilities include conducting A/B tests, analyzing data, collaborating cross-functionally, and building reusable libraries while maintaining thorough documentation.
Summary Generated by Built In
Join a leading fintech company that’s democratizing finance for all.

Robinhood Markets was founded on a simple idea: that our financial markets should be accessible to all. With customers at the heart of our decisions, Robinhood and its subsidiaries and affiliates are lowering barriers and providing greater access to financial information. Together, we are building products and services that help create a financial system everyone can participate in.

With growth as the top priority...

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. If you’re invigorated by our mission, values, and drive to change the world — we’d love to have you apply.

About the team + role

The mission of the Applied Machine Learning 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.  As we embark on this exciting journey, we are looking for a senior Machine Learning Engineer to join us to make this vision a reality.

What you'll do

As a Machine Learning Engineer on our team, your primary focus will be on the implementation and evaluation of machine learning algorithms through rigorous experimentation and testing methodologies. Your responsibilities will include:

  • 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. .

What you bring

  • 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.
  • Proven experience in ML with a focus on ranking, recommendation systems, multi-objective optimization, and reinforcement learning.
  • Proficiency in Python, SQL, XGboost, PyTorch/TensorFlow.
  • Experience with Spark, Kafka, and Kubernetes is also desirable.
  • Ideally you have experience in the Finance sector.

What we offer

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


We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on September 19, 2024.

Please see the independent bias audit report covering our use of Covey here.

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)

$187,000$220,000 USD

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

$165,000$194,000 USD

Zone 3 (Lake Mary, FL)

$146,000$172,000 USD

Click here to learn more about available Benefits, which vary by region and Robinhood entity.

We’re looking for more growth-minded and collaborative people to be a part of our journey in democratizing finance for all. If you’re ready to give 100% in helping us achieve our mission—we’d love to have you apply even if you feel unsure about whether you meet every single requirement in this posting. At Robinhood, we're looking for people invigorated by our mission, values, and drive to change the world, not just those who simply check off all the boxes.

Robinhood embraces a diversity of backgrounds and experiences and provides equal opportunity for all applicants and employees. We are dedicated to building a company that represents a variety of backgrounds, perspectives, and skills. We believe that the more inclusive we are, the better our work (and work environment) will be for everyone. Additionally, Robinhood provides reasonable accommodations for candidates on request and respects applicants' privacy rights. Please review the specific Robinhood Privacy Policy applicable to the country where you are applying.

Top Skills

A/B Testing
Machine Learning
The Company
HQ: Menlo Park, CA
3,464 Employees
Hybrid Workplace
Year Founded: 2013

What We Do

Robinhood was founded on a simple idea—that our financial markets should be accessible to all. In an industry where barriers have prevailed for too long, this hasn’t always been easy. We’re leveling the playing field by making trading more intuitive, more affordable, and more inclusive to ensure that everyone, regardless of wealth or industry knowledge, feels empowered to participate in the financial system.

Full Disclosures: rbnhd.co/social_media_disclosures

Why Work With Us

Robinhood looks to hire employees who embody a high-growth mindset, set ambitious goals, make decisions independently, and who show up as accountable. The work moves fast, and resilience is key. Maintaining grit, perseverance, and self-motivation are critical to an employee's success at Robinhood, but so is staying humble and sharing credit.

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