Robin Hu
@robinhu1
Staff Software Engineer specializing in scalable ML infrastructure and experimentation platforms.
United StatesWhat I'm looking for
I am a Staff Software Engineer who architects scalable ML infrastructure and experimentation platforms that power high-traffic services and drive measurable revenue impact. I led the development and adoption of a central Feature Store and ML Experimentation Platform used by 200+ teams, built real-time ingestion with sub-100ms latency, and integrated automated anomaly detection and canary rollbacks to keep models healthy in production.
I have a proven track record migrating monoliths to event-driven microservices, establishing SLOs and observability standards, and mentoring engineering teams to adopt CI/CD and reliability practices. My work on personalization, search refinement, payments data platforms, and production ML pipelines delivered improved latency, reduced incidents, faster model deployment, and significant business outcomes.
Experience
Work history, roles, and key accomplishments
Architected and launched a central Feature Store and ML Experimentation Platform adopted by 200+ teams, enabling online inference with sub-100ms feature ingestion and driving measurable conversion and revenue gains; established SLOs, monitoring, and CI/CD practices that reduced incidents and MTTD significantly.
Led an 18-month migration of a monolithic Search Refinement service (100M+ DAU) to event-driven microservices on AWS, improving p99 latency and enabling independent team ownership through clear domain boundaries and SLO-driven reliability.
Contributed to a PCI-DSS compliant data lake and built orchestration and inference pipelines that cut data readiness from 5 days to under 8 hours and reduced fraud model deployment time from 3 weeks to 3 days, reducing payment fraud losses by 15%.
Education
Degrees, certifications, and relevant coursework
Case Western Reserve University
Bachelor's Degree, Computer Science
2005 - 2009
Completed a Bachelor's degree in Computer Science with coursework in software engineering, distributed systems, and algorithms.
Tech stack
Software and tools used professionally
Amazon API Gateway
D3.js
Stackdriver
AWS Step Functions
Kubernetes
MySQL
PostgreSQL
MongoDB
Node.js
Django
Spring Boot
Next.js
Tailwind CSS
Material-UI
Redis
Terraform
Jira
Vue.js
JavaScript
Java
ES6
TensorFlow
PyTorch
Kafka
FastAPI
Grafana
Prometheus
Datadog
Gemini
GraphQL
gRPC
Elasticsearch
Deepgram
LangChain
LlamaIndex
100ms
Increase
Availability
Location
United StatesAuthorized to work in
Job categories
Skills
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