Built

Compensation

Full Description

Job Description: • Build and operationalize the infrastructure that allows machine learning to run reliably in production. • Architect and implement Built’s foundational ML Ops platform from scratch • Define and deploy reusable patterns for model training, deployment, monitoring, and retraining • Build CI/CD pipelines for ML lifecycle automation, including versioning and experimentation tracking • Stand up a feature store integrated with Snowflake and AWS to support structured and unstructured data • Implement model registry and governance standards to ensure reproducibility, auditability, and rollback capability • Integrate ML workloads into our event-driven architecture (Kafka, Kinesis) • Develop observability frameworks to monitor drift, performance, latency, and model quality in production • Automate ML infrastructure using Terraform and AWS-native tooling (SageMaker, Lambda, ECS, Batch, Step Functions) • Establish security and compliance standards across ML assets, including data lineage and access control • Mentor engineers on ML Ops patterns and deployment best practices Requirements: • Experience architecting and deploying ML systems in production environments • Deep familiarity with ML lifecycle automation (training, CI/CD, deployment, monitoring) • Strong AWS experience, particularly within ML pipelines (SageMaker preferred) • Proven experience building infrastructure-as-code solutions (Terraform) • Experience productionizing ML workflows end-to-end, not just optimizing existing systems • Strong Python proficiency • Experience integrating ML workloads with data platforms and event-driven systems • Solid SQL skills and familiarity working with Snowflake. Benefits: • Competitive benefits including: uncapped vacation, health, dental & vision insurance • 401k with match and expedited vesting • Robust compensation package, including equity in the form of stock options • Flexible working hours, paid family leave, ERGs & Mentorship opportunities • Learning grant program to support ongoing professional development