Solutions Architect - MLOps & Real-Time Data Integration

Overview

Solutions Architect focused on MLOps and real-time data integration, designing and implementing scalable streaming and AI-enabled architectures.

What you'll do

• Design and implement scalable real-time data integration and Change Data Capture (CDC) solutions using the Striim platform.
• Build streaming architectures connecting enterprise databases, cloud data platforms, messaging systems, and AI/ML environments.
• Develop data pipelines for machine learning workflows including feature engineering and real-time model inference.
• Create proof-of-concepts, reference architectures, and deployment patterns for enterprise use.
• Configure, optimize, and troubleshoot data pipelines across cloud and hybrid environments.
• Participate in architecture reviews, implementation planning, and production readiness activities.

What you'll need

• 2+ years of professional experience or equivalent graduate research, internships, or project experience in relevant fields.
• Strong foundation in data science concepts including machine learning algorithms and the machine learning lifecycle.
• Understanding of MLOps practices such as model deployment, inference, monitoring, versioning, and CI/CD for ML.
• Exposure to ML frameworks/platforms including MLflow, Kubeflow, Vertex AI, SageMaker, or Azure Machine Learning.
• Familiarity with data integration concepts including CDC, event-driven architectures, and real-time streaming pipelines.
• Working knowledge of relational and NoSQL databases, including SQL proficiency.
• Experience with cloud platforms such as AWS, Azure, GCP, Databricks, Snowflake, BigQuery, Redshift, or Azure Synapse.

Details

• Location: United States - Remote.