Principal ML Architect — Real-Time, Large-Scale ML

Openkrill; United States; Remoto; USD 196.000 - 246.000; Tempo pieno

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Descrizione del lavoro

Openkrill is seeking a senior ML Architect to lead the next generation of high-scale ML systems. You will shape architectures spanning data prep, feature generation, model delivery, deployment, serving and monitoring, ensuring reliability at billions of transactions per day.

You'll influence ML production practices, collaborate across data science, software engineering and business stakeholders, and drive architectural direction in a growth-focused, risk-balanced environment.

Competenze

• Master's or PhD in a STEM field or equivalent depth of experience in data science, ML engineering, ML architecture or related roles.
• Proven ability to move ML from experimentation to production environments.
• Deep knowledge of production ML infrastructure and pipelines (MLOps).

Mansioni

• Design end-to-end architectures for large-scale ML systems including data prep, feature generation, model delivery, deployment and monitoring.
• Create solutions for validating and transforming large datasets to ensure high-quality inputs for models.
• Lead model delivery and ensure reliable movement from development to production.
• Develop scalable deployment and hosting approaches for ML models.
• Establish robust monitoring and management of deployed models and supporting systems.
• Identify optimization opportunities across data processing, model execution and serving infra.
• Provide architectural direction across ML initiatives and collaborate with stakeholders.
• Apply strong software engineering principles to ML system design for production-grade results.

Conoscenze

ML Architecture

MLOps

Production ML

Data Pipelines

Model Deployment

Cross-functional

Software Engineering

Performance Optimization

Statistics & ML

System Design

Formazione

Masters/PhD in STEM

Descrizione del lavoro

Openkrill is seeking a senior ML Architect to lead the next generation of high-scale ML systems. You will shape architectures spanning data prep, feature generation, model delivery, deployment, serving and monitoring, ensuring reliability at billions of transactions per day.

You'll influence ML production practices, collaborate across data science, software engineering and business stakeholders, and drive architectural direction in a growth-focused, risk-balanced environment.