Overview
Machine Learning Engineer role focused on deploying and operationalizing core data science and AI models for the Global Mobility Solution platform, including monitoring, benchmarking, and production scaling.
What you'll do
- Contribute to building an ML Operations platform.
- Support model deployment into production platforms and manage model artifacts and serving/inference pipelines.
- Implement monitoring, logging, and observability for reliability and performance.
- Build and manage containerized deployment environments.
- Evaluate and integrate cloud-native services, distributed computing frameworks, and infrastructure automation tools.
- Collaborate with data scientists and engineers to support, troubleshoot, and optimize AI model productionalization.
- Transform proof-of-concept models into production-ready solutions and deploy at scale.
What you'll need
- Bachelor degree in Computer Science; Master preferred.
- 3+ years of experience deploying, monitoring, and maintaining machine learning models in cloud environments.
- Fluency in English.
- Demonstrated experience with AWS, Terraform, and Kubernetes.
- Demonstrated experience with MLOps (machine learning lifecycle).
- Programming and engineering tools such as Python, Git, unit testing, and CI/CD principles.
- Experience with Linux, Bash, Docker, and Airflow for containerization and workflow orchestration.
- Experience with data storage/ingestion/processing such as SQL, NoSQL, data lakes, object storage, and batch/streaming pipelines.
- Ability to function independently and in a collaborative team environment.
Read the full description and apply on the company’s own careers page.
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