United States onlyThis is a remote position.
environment. We are looking for a highly motivated individual who can develop
cutting edge MLOps and DevOps frameworks to deploy AI models. The candidate
should have a solid grasp of state-of-the-art cloud technologies, best in class
deployment architectures/frameworks and production grade software. Finally, the
role requires strong team and interdisciplinary collaboration to see products
through the development cycle from beginning to end.
Core Job Responsibilities:
Develop end-to-end pipelines encompassing the ML lifecycle from data ingestion,
data transformation, model training &validation, model deployment & serving,
and model evaluation over time.
Collaborate closely with AI scientists to accelerate productionization of ML
algorithms.
Setup CI/CD/CT pipelines for ML algorithms.
Deploy models as a service both to cloud and on-prem edge.
Manage a team of DevOps/MLOps engineers.
Learn and apply new tools, technologies, and industry best practices.
Requirements
Key Qualifications
MS in Computer Science, Software Engineering, or equivalent field
Experience with Cloud Platforms, especially GCP, and related skills: Docker,
Kubernetes, edge computing.
Familiarity with task orchestration tools, such as MLflow, Kubeflow, Airflow,
Vertex AI, Azure ML, etc.
Fluency in at least one general purpose programming language, Python
preferred.
Strong DevOps skills: Linux/Unix environment, testing, troubleshooting,
automation, Git, dependency management, and build tools (GCP Cloud Build,
Jenkins, Bazel, Gitlab CI/CD, Github Actions, etc.).
Data engineering skills a plus, such as Beam, Spark, Pandas, SQL, Kafka, GCP
Dataflow, etc.
5+ years of experience, including academic experience, in any of the above.
3+ years of managing a DevOps/MLOps team.
Benefits
Best in the industry
