Senior Machine Learning Engineer, AI Platform
Tasks
- Design and manage GPU based inference and training workloads
- Design build and operate AI platform components for ML model training deploy and serving
- Implement observability metrics logging tracing and alerting for ML services
- Improve model lifecycle packaging versioning testing validation and deployment automation
- Optimize inference systems for throughput latency and cost
- Own model serving and inference workflows
- Participate in incident response on call rotations and post incident reviews
- Partner with product infrastructure security and data teams for scalable platform capabilities
- Propose architectural improvements and mentor engineers through code reviews
Perks/Benefits
- Accidental death and dismemberment
- Birthday day off
- Country specific holidays
- Disability insurance
- Employee assistance program
- Employee referral bonus
- Home office stipend
- Life insurance
- Medical, dental, and vision coverage
- Paid disability coverage
- Paid parental leave
- Professional development budget
- Retirement contributions
- Well-being stipend
- Wellness days
Skills/Tech-stack
Alerting | Batching | CI/CD | CUDA | Capacity Planning | Cloud Computing | Deployment Automation | Distributed Systems | Docker | GPU | Inference Pipelines | Kubernetes | Latency optimization | Logging | Machine Learning | Metrics | Model Conversion | Model Packaging | Model Serving | Observability | Performance Tuning | Python | Quantization | Resource Utilization Optimization | Resource utilization | Throughput Optimization | Tracing | Utilization Optimization | Version control
Education
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