(ML)Ops Engineer – AWS
Are you a senior cloud engineer ready to power AI, ML, and GenAI platforms on AWS at scale—from experimentation to production?
As a Senior Cloud Native (ML)Ops Engineer, you will work at the intersection of cloud infrastructure, DevOps, and machine learning operations. With 5+ years of hands-on experience, you will design, build, and operate a reliable, scalable, and secure cloud-native platform that supports data scientists and analysts throughout the full lifecycle — from experimentation to production.
You will play a key role in enabling AI, Machine Learning, and Generative AI initiatives, ensuring high performance, automation, and operational excellence across the platform.
Role
- Design, build, and operate cloud-native platform services for AI models and data pipelines
- Configure and manage AWS services, including networking, gateways, Lambda, container services, and Landing Zones
- Manage infrastructure using Infrastructure as Code (Terraform)
- Translate functional and non-functional requirements into technical designs
- Evaluate design trade-offs and ensure compliance with architecture standards
- Support deployments and ensure solutions meet business and technical requirements
- Automate data processing and model lifecycle workflows using Apache Airflow, Apache Spark, and Python
- Provide platforms and frameworks for:
- Multi-user Jupyter environments
- Cloud IDEs
- Training, storing, serving, and monitoring ML models
- Expose models via API gateways for low-latency request-response use cases
- Enable Generative AI (GenAI) and Large Language Model (LLM) initiatives
- Ensure reliability, performance, scalability, security, and cost efficiency
- Perform complex incident resolution and root cause analysis
- Maintain technical documentation and contribute to platform evolution
- Support onboarding and day-to-day platform usage by internal teams
- Participate in an on-call rotation for supported systems
Profile
Education & experience
- Master’s degree in ICT, Engineering Sciences, Business Engineering (Informatics focus), or equivalent experience
- Minimum 5 years of experience in cloud infrastructure, DevOps, or platform engineering
Required technical skills
The following skills are mandatory:
- Apache Airflow
- Apache Spark
- AWS CI/CD tooling
- AWS Kinesis Streams
- AWS Lambda
- AWS S3
- AWS SageMaker
- Docker
- GitHub / Bitbucket
- Python
- Terraform (Infrastructure as Code)
Offer
Freelance contract renewable every year
3 days remote
