Senior Machine Learning Platform/Ops Engineer
Core
Build and maintain high-reliability ML pipelines, observability systems, and cloud infrastructure to productionize machine learning models and LLM features.
Role type
Senior Machine Learning Platform/Ops Engineer
Builds
Production ML systems, LLM serving pipelines, and scalable data ingestion flows for an AI-enhanced learning platform.
Domain
Ed-Tech, Cloud Infrastructure, Machine Learning Operations
Deliverable
production ML models
Required skills
Python, SQL, ML pipeline orchestration (Airflow, Kubeflow, Dagster), Cloud platforms (GCP, AWS), Kubernetes, CI/CD, Infrastructure as Code (Terraform), Containerization (Docker)
Preferred skills
LLM serving, Vector databases, GenAI product flows, Agentic AI SDLC
Technologies
Databricks, MLFlow, Airflow, DBT, Sagemaker, Tecton, Spark, BigQuery, Kafka, Python, SQL, Terraform, Docker, Kubernetes
Responsibilities
Build and maintain ML pipelines for training, evaluation, and deployment; Support AI scientists in creating reproducible, containerized model training environments; Define and implement observability and alerting for ML systems; Design and scale data ingestion and feature transformation flows; Contribute to internal Python libraries and platform tooling; Ensure ML services are modular, testable, and monitored from day one.
Seniority
Senior, hands-on IC
