MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
About the role
- MLOps Engineer improving training pipelines and model performance for Eqvilent. Responsible for implementing CI/CD and monitoring systems in a remote work environment.
Responsibilities
- 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.
Requirements
- Strong knowledge of Python
- Familiarity with Docker
- Basic understanding of machine learning concepts and techniques
- Experience with PyTorch (a plus)
- Knowledge of Dagster (a plus)
- Experience automating ML pipelines from data ingestion to deployment with monitoring and observability (a plus)
- Experience with monitoring frameworks (Grafana, Prometheus, or similar) (a plus)
- Understanding of distributed training systems for ML models (a plus)
Benefits
- 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
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