Senior Machine Learning Engineer, AI Infra
About The Position
Robinhood is building an elite team to apply frontier technologies to the world’s biggest financial problems. The AI Infrastructure team’s mission is to provide a robust, agile, and centralized AI platform, empowering teams across Robinhood. This team partners deeply across Data, Platform, and Product Engineering to define how AI gets built and run at Robinhood, with a high bar for reliability, scalability, and craft. As a Senior Software Engineer on the AI Infrastructure team, you will be a technical anchor on the ML platform, owning the architecture and end-to-end delivery of foundational systems that power model development, deployment, and observability across the company. You will lead the design of complex platform capabilities including the feature store, model serving layer, and training infrastructure, while partnering closely with ML practitioners to ensure these systems accelerate their work. You will bring senior-level judgment to ambiguous technical problems, contribute to the team’s technical strategy, and help mentor engineers earlier in their careers. Your work will directly shape how every AI product at Robinhood gets built, scaled, and maintained in production. This role is based in our Menlo Park, CA and Bellevue, WA office(s), with in-person attendance expected at least 3 days per week. Robinhood believes in the power of in-person work to accelerate progress, spark innovation, and strengthen community. The office experience is intentional, energizing, and designed to fully support high-performing teams.
Requirements
- 6+ years of software engineering experience, with meaningful depth in ML infrastructure, data engineering, or model operations
- Demonstrated ability to own and deliver complex platform systems end-to-end, from architecture to production
- Deep expertise in model serving, distributed systems, and production ML workflows at scale
- Strong proficiency in Python, C++, or similar languages, and hands-on experience with ML frameworks such as TensorFlow or PyTorch
- Solid knowledge of modern ML infrastructure tooling (e.g., Ray, Kubeflow, SageMaker, TensorFlow Serving, Triton)
- Hands-on experience with large-scale search systems, including embedding models, vector databases, and distributed retrieval engines using platforms such as Qdrant, ChromaDB, or Elasticsearch with dense vector search capabilities
- Experience influencing technical direction across teams and mentoring engineers at varying levels
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical field
Nice To Haves
- advanced degree a plus
Responsibilities
- Lead the architecture and end-to-end delivery of scalable systems for deploying, monitoring, and managing ML models in production
- Own the technical direction for key platform areas — including model serving, the feature store, and ML observability infrastructure — from design through long-term reliability
- Drive cross-functional partnerships with ML practitioners, data engineers, and applied AI teams to streamline workflows, reduce friction, and accelerate experimentation
- Evolve and scale our feature store to support efficient, low-latency feature retrieval across real-time and batch use cases
- Define and implement robust observability standards for model performance, data pipelines, and feature freshness across the ML platform
- Manage and optimize cloud compute resources (CPU/GPU) on AWS to support cost-effective, high-throughput training and inference at scale
- Contribute to technical strategy and roadmap discussions, and help mentor engineers on the team through design reviews and hands-on guidance
Benefits
- Performance driven compensation with multipliers for outsized impact
- bonus programs
- equity ownership
- 401(k) matching
- 100% paid health insurance for employees with 90% coverage for dependents
- Access to the Robinhood Employee Fund that gives eligible US employees the opportunity to invest in a private employee fund that provides exposure to Robinhood Ventures funds.
- Access to the best AI tools on the market and continuous AI skill-building for every employee, technical or not.
- Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
- Employer-paid life & disability insurance
- fertility benefits
- mental health benefits
- company holidays
- paid time off
- sick time
- parental leave
- catered meals
- events
- comfortable workspaces
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What This Job Offers
Job Type
Full-time
Career Level
Senior
