Senior Machine Learning Engineer
Core
Build, maintain, and test architecture and infrastructure for managing machine learning applications and products.
Role type
Senior Machine Learning Engineer (Infrastructure & MLOps)
Builds
Scalable ML applications, pipelines, and infrastructure
Domain
Machine Learning Engineering, MLOps, Cloud Infrastructure
Deliverable
production ML models
Required skills
Python, Shell scripting, distributed systems, scalable architectures, ML techniques (Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch), MLOps principles, CI/CD, cloud services (Azure, AWS, GCP, Databricks), infrastructure as code, model training and deployment, monitoring and evaluation
Preferred skills
mentoring, stakeholder management, risk management, technical excellence advocacy
Technologies
Python, Shell, Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch, Azure, AWS, GCP, Databricks, Kubernetes (implied by Kubeflow/K8s context), CI/CD tools
Responsibilities
Design and drive development of robust scalable architectures for ML applications; collaborate with data scientists to translate business needs into ML systems; own development and maintenance of core functionalities including ML pipelines and model lifecycle; drive functional streams of work and ensure timely delivery; explore and implement latest ML tools and frameworks; facilitate collaborative problem solving and mentor engineers; contribute to team ML strategy; identify and address challenges in ML systems.
Seniority
Senior, hands-on IC
