- Build on a fully containerized model architecture
- Learn provisioning of applications through Infrastructure as Code
- Work with and develop a modern CI/CD model pipeline
- Structure workflows through a flow tool through DAGs
- Provision data stores and APIs unique to data science models
- Develop new forms of data applications and stores useful for DS and Act models
- Manage container and model security (Ex: Snyk, Scout)
- Other duties assigned by management
- A Master's degree with 2-5 years experience OR a Bachelor's degree with 5-8 years experience
- Computer Science degree or related field, or equivalent experience
- 2-5 years of experience as a Backend or DevOps Engineer
- Strong experience working with relational (SQL) and non-relational (NoSQL) databases
- Strong knowledge of API security models and authentication in a distributed system
- Experience with asynchronous architectures using events, workers, and job queues
- Understanding of communication patterns in a distributed system, and reliability practices
- Experience developing and maintaining lightweight containerized applications using Docker
- Understanding of the cloud and experience working with cloud-based architectures
- Writing automated unit and integration tests, strong scripting skills
- Knowledge of Agile development practices using Git and project management tools like Jira
- Solid knowledge of Unix / Linux commands and ability to work in terminal, especially server side
- Experience with GraphQL, Kubernetes, distributed compute architectures
- Experience with vector databases
- Hands-on knowledge of CI/CD with GitHub Actions or other tools like Jenkins,CircleCI, or GitLab CI/CD
- Experience with alerting and monitoring tools like Sentry, DataDog, Logstash
- Hands on experience with Azure
- Experience with Go or Scala
- Experience working at a tech start-up or financial services
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Model Ops Development Engineer - Dallas, United States - UPLAND CAPITAL GROUP INC
Description
Job Description
Job DescriptionFull Time Employment OpportunityPrimary Function:
Our Data Science and Actuarial model environment and architecture is containerized, and we are cloud based, running on Azure. We aim to be completely automated processes to build, provision, and deploy our models and products. Our models will range from standard AI and ML models, to RL, to Bayesian simulation models which will require creative problem solving and a close collaboration with stakeholders across the organization, not limited by a 'one size fits all' mindset. You will report to the Lead Model Engineer.
Duties and Responsibilities:
Experience, Education, Special Skills Required:
Bonus Skills: