Head of Machine Learning Engineering

Palo Alto
Data Science – Data Science
The Data Science team is looking to hire a Machine Learning Engineering leader to help to build our Model as a Service framework (MaaS), to set up our experimental test environment and continue support for data collection and model enhancement.
Team Mission: “To deliver models to support optimal decisions”


    • Infrastructure: Develop a scalable cloud native architecture to support “Model as a Service”.
    • Set up and maintain ML data lake (including both NoSQL and SQL).
    • Set up and maintain capacities for both batch and stream processing.
    • Set up and maintain ML microservice architecture (Kubernetes).
    • Model management: Ensure reproducibility and traceability.
    • Work closely with Core Data Science team to ensure that all work is reproducible
    • (and auditable).
    • Help developing the framework for ML experimentation including versioning of code,
    • data, hyperparameters, environments, metrics, artifacts, …
    • Support model (re)training, evaluation, deployment and monitoring.
    • Ensure capacity for easy deployment and rollback of models.
    • DevOps: Own the Ops side of CI/CD working closely with Core Data Science team.
    • Set up and maintain dev/(pre-prod)/prod environments.
    • Help develop efficient CI practices.
    • Help develop rigorous testing practices:
    • Unit test, API test, Load/Performance test
    • But also help define proper model evaluations!
    • Work towards developing automatization of DevOps process.
    • Auto-deploy, auto-testing, ….
    • Facilitate continuous improvement practices.
    • SecOps: Working with CSO to ensure cloud security and compliance.
    • VPC, Key management, Access management
    • Data encryption (at Rest, in Motion, in Use)
    • App sec (Static Scanning, Dynamic Scanning, Dependency Scanning, Container
    • Scanning, …)


    • 15+ years of Data Engineering experience with ML focus
    • PhD in Software Engineering, Computer Science , Mathematics, Statistics, Operation
    • Research or equivalent disciplines
Uniphore is a global Conversational AI technology company with offices in the U.S., India and Singapore. Uniphore believes the future of customer service is every voice being truly heard. The Company’s vision is to bridge the gap between people and machines through voice. Uniphore enables businesses globally to deliver transformational customer service by providing a platform of Conversational Analytics, Conversational Assistant and Conversational Security that changes the way enterprises engage their consumers, build loyalty and realize efficiencies.
For more information on how Uniphore delivers business value using Conversational Service Automation, please visit www.uniphore.com