Senior Data & MLOps Engineer
Tasks
- Architect scalable distributed services with orchestration
- Build feature processing and baseline computation systems
- Deploy models for prediction and detection
- Design and implement scalable data ingestion pipelines
- Develop low-latency services and offline workflows
- Develop scalable solutions for mitigation and analysis
- Implement monitoring and feedback loops
- Integrate operational signals into monitoring and diagnostics
Perks/Benefits
- Critical illness cover
- Dental insurance
- Employee assistance program
- Life insurance
- Medical insurance
- Pension contributions
- Tuition reimbursement
Skills/Tech-stack
C++ | DCGM | Data Engineering | Distributed Systems | Drift Detection | Go | Hardware monitoring | Kafka | Kinesis | Kubernetes | MLOps | Microservices | Model Deployment | Model versioning | Monitoring | NCCL | NVML | Pulsar | PyTorch | Python | Ray | Rust | Spark | Telemetry Systems | Time Series | Time Series Data | Time-Series Data Engineering | Torchnet
Education
Roles
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