AI Engineering Technical Lead
Tasks
- Architect training evaluation deployment and monitoring
- Build and optimize feature stores
- Build production AI services
- Collaborate on AI product roadmap
- Design feature engineering pipelines
- Design model serving APIs
- Develop real-time and batch inference pipelines
- Drive production reliability and scalability
- Establish automated ML testing and validation
- Implement end-to-end ML workflows
- Implement model observability
- Integrate AI pipelines with streaming and batch systems
- Lead AI system design
- Mentor engineers in ML engineering and system design
- Monitor model performance in production
- Optimize inference services for low latency and high throughput
- Set standards for reproducibility and versioning
Perks/Benefits
- 401k
- Disability benefits
- Life insurance
- Medical/Dental/Vision
- Paid Holidays
- Paid time off
- Tuition assistance
Skills/Tech-stack
APIs | Artificial Intelligence | CI/CD | Cloud platform | Data Modeling | Distributed Systems | Event Driven | Event-driven architecture | Experimentation | Fault Tolerance | Feature Engineering | Google Cloud | Google Cloud Platform | Java | Kafka | Kubernetes | Language Processing | Low Latency | Low-Latency Systems | Machine Learning | Microservices | Model Evaluation | Natural Language | Natural Language Processing | Observability | Personalization | Pub/Sub | PyTorch | Python | Ranking Models | Real Time | Real-time Inference | Recommendation Systems | Streaming Data | TensorFlow
Education
N/A
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