Description

Design and implement scalable backend architectures and infrastructure for machine learning products across the full lifecycle.

This role is remote.

Responsibilities

• Build and operationalize AI/ML services including data ingestion, feature engineering, model integration, real-time inference, and batch processing.
• Partner with Data Scientists to productionize machine learning models and enhance feature store workflows.
• Implement streaming and batch data processing workflows at scale using infrastructure-as-code and CI/CD pipelines.
• Optimize latency, scalability, and reliability of ML systems supporting personalization, recommendation, search, and conversational AI.
• Collaborate with Data Engineering, Architecture, Governance, and Security teams to support cloud-native ML infrastructure.

Required Skills

• 5+ years of software engineering experience implementing cloud-native product solutions.
• Strong expertise in Python, SQL, PySpark, and Docker.
• Strong experience with AWS and Google Cloud Platform (GCP).
• Proven experience building backend systems supporting ML/algorithmic products.
• Experience building streaming and batch data architectures at scale.
• Strong system design and backend architecture experience.
• Experience operating in Agile environments.

Preferred Skills

• Experience contributing to system design discussions and technical architecture decisions.

Key Skills

Education

Bachelor's degree