Machine Learning Engineer
Tasks
- Build and optimize feature pipelines
- Build and train deep learning models from scratch
- Collaborate cross-functionally with product and platform teams
- Implement MLOps practices
- Mentor engineers on experimentation and deployment
- Monitor models in production
- Optimize inference performance
- Own full ML training stack
- Track experiments and manage model versioning
- Train large models on GPU infrastructure
- Translate prototypes into production ML systems
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Spark | Attention Mechanisms | Automated retraining | CI/CD | Contrastive Learning | Data-parallel | Databricks | Deep learning | Distributed Data Parallel | Distributed data | Efficient Attention | Event Tokenization | Experiment tracking | FSDP | Gradient Accumulation | Gradient Checkpointing | Inference Optimization | MLOps | Masked Modeling | Mixed Precision | Mixed-precision training | Model versioning | Positional Embeddings | Production Monitoring | PyTorch | Python | Responsible AI | Self-Supervised Learning | Self-supervised | Supervised Learning | Temporal Embeddings | TensorFlow | Transformer
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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