Staff Machine Learning Engineer
US CA San Jose - River Oaks Pkwy, United States
USD 155K-175K Senior-level Full Time Found 4d ago
Tasks
- Architect and implement scalable ML pipelines for training validation deployment and monitoring
- Collaborate with data software and product teams to integrate ML solutions into production
- Develop and optimize ML models leveraging NLP Computer Vision and Generative AI
- Drive development of ML infrastructure ensuring low-latency inference and efficient resource utilization
- Enhance model reliability through automated monitoring CI/CD pipelines and versioning
- Implement MLOps practices automating model training validation deployment and performance monitoring
- Lead data acquisition and preprocessing to improve model accuracy
- Optimize ML models for performance scalability and efficiency using techniques like quantization pruning and distributed training
- Stay updated with ML research and integrate new techniques into production systems
Perks/Benefits
- Achievement days off
- Flexible work schedule
- Health benefits
- Holidays off
- Paid family leave
- Remote options
- Unlimited personal time off
- Volunteer days
Skills/Tech-stack
AI Deployment | AI Platform | AWS SageMaker | Analytics | Azure ML | CI/CD | Computer Vision | Data Processing | Distributed Training | Docker | Evaluation | Generative AI | Google AI | Google AI Platform | Hadoop | Inference | Kubernetes | LLMs | Language Processing | MLOps | Model Serving | Model Training | Model versioning | Natural Language | Natural Language Processing | ONNX | Optimization | PyTorch | Python | R | SQL | Spark | TensorFlow | Triton
Education
Language: en |
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