In this role you will build optimized, efficient and reliable products, services and interfaces to federate access to data stores, simplify, automate and manage the ML development and deployment ecosystem. Specifically, you will develop tooling and services to deploy, host and serve ML models at scale.
Responsibilities:
- Design and develop infrastructure for the full cycle of machine learning such as workflow management, feature store, data discovery tools, and feature libraries.
- Implement backend microservices for large scale distributed systems using gRPC or REST.
- Lead and drive vision for one or more of ML Platform services.
- Drive and maintain a culture of quality, innovation and experimentation.
- Work in an Agile environment that focuses on collaboration and teamwork.
Basic Qualifications:
- Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.
- 5+ years of software experience, with 3+ years of relevant ML experience.
- Experienced with cloud technologies in AWS or GCP and container systems such as Docker or Kubernetes.
- Expertise in OO programming, either Python or Java.
- Excellent communication and people engagement skills.
Preferred Qualifications:
- Familiarity with Java or Python development ecosystem.
- Knowledge of technologies like Databricks, S3, Spark.
- Experience with graph-based data workflows such as Apache Airflow, Meson.
- Mentor colleagues on best practices and technical concepts of building large scale solutions.
This is a remote position.
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