MLOps Engineer
RemoteRemoteFull-time
AI Summary
An MLOps engineer builds and improves pipelines for training ML models, ensures data quality, tests models, and implements monitoring and CI/CD for ML services.
About this role
We are looking for an experienced MLOps Engineer to join our team. In this role, you will be responsible for improving pipelines for training machine learning models, processing and checking data quality, testing models and ensuring their correctness, and building model monitoring systems. The ideal candidate should be intelligent, contemplative, and composed. They should not rush through tasks, instead diving deeply into the code and being attentive to details.
WHAT YOU’LL BE DOING:
- Design and build ELT pipelines for data processing and analysis.
- Construct MLOps pipelines for automated retraining and validation of models.
- Implement CI/CD pipelines for deploying models and ML services.
- Create services for monitoring ML models in production.
WHAT WE LOOK FOR IN YOU:
- Strong knowledge of Python
- Familiarity with Docker
- Basic understanding of machine learning concepts and techniques
WHAT WILL BE A PLUS:
- Experience with PyTorch
- Knowledge of Dagster
- Experience automating ML pipelines from data ingestion to deployment with monitoring and observability
- Experience with monitoring frameworks (Grafana, Prometheus, or similar)
- Understanding of distributed training systems for ML models
WHY SHOULD YOU JOIN OUR TEAM?
- Great challenges with many opportunities to prove yourself
- A welcoming group of highly qualified international professionals
- Great corporate culture with internal events and surprising commitment to fostering a supportive and empowering environment
- Cutting-edge hardware and technology
- Work remotely from anywhere in the world
- Access any of our global offices anytime
- 40 paid days off
- Competitive salary
Skills
CI/CDDagsterData ProcessingDistributed Training SystemsDockerELT PipelinesGrafanaMachine Learning ConceptsMLOps PipelinesModel MonitoringObservabilityPrometheusPythonPyTorch
