Senior Machine Learning Operations (MLOps) at Talkdesk (Remote)
At Talkdesk, we are courageous innovators focused on redefining customer experience, making the impossible possible for companies globally. We champion an inclusive and diverse culture representative of the communities in which we live and serve. And, we give back to our community by volunteering our time, supporting non-profits and minimizing our global footprint. Each day, thousands of employees, customers and partners all over the world trust Talkdesk to deliver a better way to great experiences.
We are recognized as a cloud contact center leader by many of the most influential research organizations, including Gartner and Forrester. With $498 million in total funding, a valuation of more than $10 Billion, and a ranking of #17 on the Forbes Cloud 100 list, now is the time to be part of the Talkdesk legacy to help accelerate our success in a new decade of transformational growth.
- Strategize, design, build, harden, and maintain the core infrastructure used to operate our machine learning platform and lifecycle
- Be part of the senior team responsible for defining our technology strategy, roadmap and priorities for our organization
- Manage the automation of every aspect of our infrastructure to remove as much as possible any human intervention
- Keep existing base infrastructure running smoothly
- Drive and promote protocols on production readiness and operational excellence
- Partner with product engineering teams to debug production outages and carry out action items to improve the reliability of those systems
- Lead design reviews and production reviews for new features, products, or pieces of infrastructure
- Plan for the growth of Talkdesk's infrastructure
- MLOps experience in a high data volume environment, 5+ years, enterprise-level company preferred
- MLOps or Senior Site Reliability Engineering leadership experience in a software engineering organization with several stakeholders
- Experience with Operation Processes implementing ITSM tools and workflows for incident response, change and problem management.
- Experience monitoring model performance in production
- Experience with data lake platforms such as Databricks or Snowflake
- Experience with Linux/Unix systems / Terraform
- Ability to identify time consuming and error prone manual tasks and then manage the building of a tooling to automate them
- Understand large-scale complex systems from a reliability perspective
- Ability to identify root causes of instability in a large-scale distributed system, across stacks
- Hold yourself and others around you to high standards when working with production
- Experience with cloud-based solutions such as Amazon AWS, Google Cloud, or Microsoft Azure
- Experience in a SaaS environment with technologies such as Docker, Consul, Vault, Jenkins, Concourse, Prometheus, Nexus
- Experience with messaging systems such as RabbitMQ or Kafka
- Operational knowledge with various data stores such as MongoDB, Postgres, Redis, Cassandra, Elasticsearch
- Experience with configuration management software such as Ansible or Chef
- Knowledge of security controls and frameworks from standards such as SOC2, ISO, GDPR, FedRAMP, etc.