Senior Machine Learning Engineer
Tasks
- Design A/B tests and evaluate models
- Design real-time inference APIs
- Develop and deploy ML models
- Ensure system latency and throughput
- Handle large-scale datasets
- Implement deep learning architectures
- Maintain data lineage and reproducibility
- Manage MLOps pipelines
- Monitor model performance
- Perform feature engineering
- Scale data pipelines
- Write scalable production code
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | APIs | B testing | C++ | CI/CD | CatBoost | Data Drift | Data Drift Detection | Data Processing | Distributed Computing | Drift Detection | Experiment design | Factorization machines | Flink | Go | Gradient boosting | Hypothesis Testing | Inference Server | Java | Kafka | LightGBM | Low Latency | Low-Latency Systems | MLOps | Microservices | Model Deployment | Model retraining | Model versioning | Neural Networks | ONNX | PyTorch | Python | Ray | Realtime systems | Recommendation Systems | Rust | SQL | Scala | Spark | Statistics | TensorFlow | TensorRT | Triton Inference | Triton Inference Server | XGBoost
Education
Regions
Countries
States
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