Role overview
A client based in Arlington, VA is seeking a Senior MLOps Engineer to join their team in a contract-to-hire capacity, hybrid role, requiring 2–3 days per week in the office. The primary focus of this role is to build and optimize infrastructure for deploying, packaging, observing, and retraining machine learning models. This is not a model development role, but one centered on operationalizing existing models. The company specializes in providing transparent, customized financing solutions to small businesses, helping them access capital through a range of loans, credit, and factoring products.
**Key Responsibilities**
* Set up and manage infrastructure for ML model deployment and monitoring.
* Package, version, and automate ML workflows using tools such as MLflow and CI/CD pipelines.
* Enable retraining pipelines and integrate with platforms like AWS SageMaker and Snowflake.
* Collaborate with existing data teams; no data warehousing responsibilities are expected.
**Required Skills & Tools:**
* Proficiency in Python, Docker, and Kubernetes.
* Hands-on experience with MLflow, SageMaker, and CI/CD pipelines.
* Familiarity with GitHub and Snowflake’s ML features.
* Understanding of data warehousing concepts (execution is handled by other vendors).
**Benefits:**
* Health, Dental, Vision Insurance
* 401k
* Paid Sick Time
* Commuter Benefits
**Posted By:**
Carson Khadka