Quick Reminder - MLops Lead - New York, NY - Hybrid

Overview

On Site
Full Time

Skills

AWS
Python
Kubernetes
Terraform
GCP
ML frameworks

Job Details

Role: MLops Lead

Location: New York, NY Hybrid

Fulltime Role

Job description:

The ML Ops Lead drives the design, deployment, and optimization of machine learning solutions, balancing hands-on engineering with strategic leadership to enable robust, scalable, and maintainable AI infrastructure.

Key Responsibilities

  • Architect and maintain scalable ML infrastructure, self-service ML pipelines, and CI/CD workflows for model training and deployment.
  • Lead and mentor an MLOps team, fostering technical excellence and continual improvement.
  • Design high-scale distributed training and inference environments using cloud (AWS, Google Cloud Platform) and on-premises resources.
  • Build and manage feature stores, data ingestion, preprocessing, and validation pipelines.
  • Implement A/B testing, canary releases, monitoring, and rollback mechanisms for production ML models.
  • Ensure compliance with data governance, privacy, and security standards; manage role-based access controls for ML infrastructure.
  • Collaborate with data scientists, software engineers, DevOps, and product teams to bring models from experimentation to enterprise-grade production.

Required Skills and Experience

  • Deep expertise in creating and managing machine learning infrastructure and orchestration frameworks (e.g., Kubeflow, MLflow, Airflow).
  • Proficiency in cloud platforms (AWS, Google Cloud Platform), Kubernetes, Terraform, and distributed computing.
  • Excellent skills in Python and ML frameworks (TensorFlow, TorchServe), CI/CD automation, and pipeline management.
  • Strong analytical, problem-solving, and project management abilities.
  • Demonstrated ability to build, scale, and lead technical teams.
  • Solid understanding of data compliance, governance, and model monitoring.

Desired Qualifications

  • Experience optimizing GPU/TPU utilization and large-scale storage solutions.
  • Track record in designing robust monitoring systems for model drift, downtime, and performance.
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