Sr. ML Ops Engineer
Corvus RoboticsAI & company
RemoteSenior
Y Combinator
S2G Ventures
Spero Ventures
Cathexis Ventures
One Way Ventures
Catalyst Investors
Data & AI
About the role
TL;DR
Build data infrastructure and tools for ML team to accelerate model development.
- •We're hiring a systems-oriented Senior Software Engineer to build the data infrastructure, training pipelines, and internal tooling that our ML team needs to move faster.
- •Key Responsibilities Build and maintain the data pipeline infrastructure that consolidates internal infra, labeling tools, S3, and other data sources into a unified, queryable system Build tooling for dataset selection and curation that can programmatically target specific data (by environment, object type, etc.) Own ML data infra from robot to training run, accessible to the ML team without backend engineering help Build model evaluation and regression testing infrastructure -
- •real metrics, not vibes or "someone complained in prod" Automate the model retuning loop for standard tasks so ML engineers can be mostly hands-off on routine updates Requirements 2-3 years shipping real production ML infrastructure for big datasets, not just scripts Experience building distributed data pipelines that consolidate multiple sources Demonstrated understanding of data flow from raw collection, labeled training set, to trained models Experience building systems from scratch, or contributed heavily to a small-team infra build where the playbook didn't exist Ability to thrive in a startup environment with high ambiguity.
- •You'll figure out what to build
Required skills
PythonAirflowPandasNumPyAWSS3Kubeflow
Nice-to-have skills
MLflowSageMakerVertex AIONNXJAXHugging FaceComputer VisionNLPLLMsLangChain
Domain expertise
ai
Tech stack
KubeflowPythonAirflowPandasNumPyAWSS3
