Machine Learning Engineer
Tasks
- Build time series forecasting and anomaly detection models
- Collaborate with system administrators and data engineers
- Create data pipelines from telemetry and logs
- Deploy machine learning models on Kubernetes
- Design and develop machine learning models
- Detect anomalies for cybersecurity use cases
- Develop scalable inference services
- Operationalize model lifecycle management
- Participate in agile scrum ceremonies
- Validate models for production readiness
Perks/Benefits
- Flexible work schedule
- Half-day Fridays
- Intensive summer workday
- Learning and growth
- Work-life balance
Skills/Tech-stack
Agile | Anomaly Detection | Classification | Confluence | Containerization | Data pipeline | Deep learning | Distributed Systems | Feature Engineering | GPUs | Git | GitHub | GitLab | HPC | Infiniband | Jira | Kubernetes | Linux | Logs | Machine Learning | Metrics | Predictive Maintenance | Prometheus | PyTorch | Python | Scikit-learn | Scrum | Series forecasting | Telemetry | TensorFlow | Time Series | Time Series Forecasting
Education
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