Machine Learning Engineer
Tasks
- Analyze HR and Finance text data
- Build graph based recommendation systems
- Build machine learning pipelines
- Create Docker Kubernetes hosted APIs and services
- Deploy and manage model services
- Design scalable ML architectures
- Develop LLM applications
- Develop RAG solutions
- Develop information retrieval systems
- Evaluate scalability and observability
- Perform data preprocessing and wrangling
- Train, fine-tune, and evaluate models
Perks/Benefits
Skills/Tech-stack
AWS | Cloud Computing | Data Wrangling | Deep learning | Docker | Fine Tuning | GCP | Graph Based Recommendation | Graph-based | Information Retrieval | Kubernetes | Language Models | Language Processing | Large Language Models | Machine Learning | Model Deployment | Model Evaluation | Model Fine-tuning | Natural Language | Natural Language Processing | Pandas | PySpark | PyTorch | Python | Retrieval-Augmented Generation | Scikit-learn | Statistical Analysis | Supervised Learning | TensorFlow | Text Generation | Unsupervised Learning
Education
Regions
Countries
States
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