Senior AI/MLOps Engineer

Role Overview

We are looking for a Senior AI/MLOps Engineer to provide technical leadership in the development and operation of scalable machine learning infrastructure and production ML systems.

The role focuses on designing and improving machine learning pipelines, supporting both real-time and batch inference, and ensuring reliable deployment and operation of models in production. The engineer will work closely with Data Science and engineering teams to optimize ML systems, introduce new technologies, and develop scalable long-term solutions.

The position also includes mentoring other engineers, conducting code reviews, establishing engineering best practices, and collaborating with both technical and non-technical stakeholders.

Responsibilities

• Provide technical leadership and mentorship to Machine Learning Engineers.
• Design, architect, and oversee complex machine learning pipelines and production ML infrastructure.
• Develop and maintain systems supporting both real-time and batch inference.
• Collaborate with Data Science teams to deploy, monitor, and optimize machine learning models in production.
• Improve the performance, scalability, reliability, and maintainability of ML systems.
• Establish and promote best practices across software development, DevOps, and MLOps.
• Conduct code reviews and provide technical guidance to engineering teams.
• Evaluate and integrate new technologies and tools into the ML infrastructure.
• Work with technical and non-technical stakeholders to translate complex ML concepts into practical solutions.
• Contribute to the long-term technical direction of machine learning platforms and infrastructure.

Technologies & Tools

• Cloud: AWS or other major cloud platforms
• Containers & Orchestration: Kubernetes
• MLOps: MLflow, model deployment, monitoring, and lifecycle management
• Workflow Orchestration: Airflow or Dagster
• Data & Streaming: Kafka and stream-processing technologies
• Programming: Python, SQL
• Engineering Practices: Software development, DevOps, MLOps, CI/CD, production system design
• Machine Learning: Model design, deployment, optimization, and maintenance at scale

Requirements

• Senior-level experience in AI/ML engineering, MLOps, or a related field.
• Strong experience designing and operating production machine learning systems.
• Solid understanding of ML pipelines, model deployment, and production inference.
• Strong programming skills in Python and SQL.
• Experience with cloud infrastructure, preferably AWS.
• Experience with Kubernetes and containerized environments.
• Experience with MLflow and workflow orchestration tools such as Airflow or Dagster.
• Understanding of streaming and data-processing technologies such as Kafka.
• Strong communication and collaboration skills.
• Ability to provide technical leadership, mentor engineers, and drive engineering best practices.