Data / MLOps Engineer
Pipelines, containers, CI/CD and model tracking for small teams shipping models into production.
What you would do
- Own the data and training pipelines behind our computer vision work: ingestion, validation, versioning, scheduled retraining.
- Containerize models and services, and build the CI/CD that tests and deploys them.
- Run the model registry and experiment tracking so that every deployed model can be traced to its data, code and metrics.
- Pair with a vision engineer so that the two of you can cover a full statement of work.
What we screen for
The screening exercise measures exactly these three things.
- Pipelines you have run in production, including what broke and how you found out.
- Docker and CI/CD fluency: reading a Dockerfile and a pipeline definition and seeing what is wrong.
- Working knowledge of a model registry or experiment tracking system, and why it exists.
Requirements
- Two to four years of experience in data engineering, MLOps or platform engineering.
- Authorized to work in the United States. Some of the work this role supports requires United States person status.
- This role is deliberately for a pipelines and infrastructure specialist. Vision experience is welcome but is not what we are hiring for here.
Questions or accommodations: careers@di-ds.com. DI-DS is an equal opportunity employer.