Artificial Intelligence / Machine Learning Data Engineer
USD 80K-176K (estimate) Mid-level Full Time
Tasks
- Build ETL feature engineering and model training pipelines
- Create analytics dashboards and business intelligence solutions
- Deploy fine-tuned large language models
- Design data lakes data warehouses and real time streaming architectures
- Design distributed inference for degraded network conditions
- Design edge optimized model deployment with optimization
- Develop computer vision pipelines for object detection tracking classification
- Develop conversational AI interfaces with open source large language models
- Enforce data quality standards validation checks and governance
- Implement CUDA and TensorRT hardware acceleration
- Implement multi-modal sensor fusion algorithms
- Implement retrieval augmented generation systems
- Implement testing and validation for machine learning models adversarial testing degraded data scenarios
- Optimize AI workloads for embedded platforms
- Profile and optimize edge device memory and power usage
Perks/Benefits
- Access to cutting-edge hardware
- Conference attendance support
- Flexible work arrangements
- Professional development
- Rapid prototyping environment
- Remote work hybrid flexibility
Skills/Tech-stack
Anomaly Detection | Apache Airflow | Apache Spark | CUDA | Computer Vision | DBT | Data Lakes | Data Warehouses | Diffusion Models | ETL | Embeddings | Explainable AI | Feature Engineering | Grafana | JAX | Knowledge graphs | Kubeflow | LLM Deployment | Langchain | ML metadata | MLOps | MLflow | Model Training | NoSQL | ONNX | OpenCV | PGVector | PIL | Pinecone | PowerBI | PyTorch | Python | Quantization | Real Time | Real-time Streaming | Retrieval-Augmented Generation | SQL | Sensor fusion | Series analysis | Tableau | TensorFlow | TensorRT | Time Series | Time Series Analysis | Transformers | Vector Databases | Weaviate | Weights and Biases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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