Machine Learning Engineer
22 hours ago
Key Responsibilities:
Generative AI Solutions:
Utilize machine learning and AI technologies to build and fine-tune models such as GANs, VAEs, and Transformers.
Classical ML Models:
Design and develop machine learning models (regression, decision trees, SVMs, random forests, gradient boosting, clustering, dimensionality reduction) to address complex business challenges.
Deep Learning Systems:
Train, fine-tune, and deploy deep learning models such as CNNs, RNNs, LSTMs, GANs, and Transformers to solve AI problems and optimize performance.
- Participate in Natural Language Processing activities, refining and optimizing prompts to improve outcomes for Large Language Models (LLMs), such as GPT, BERT, and T5.
- Work with large datasets, perform data preprocessing, augmentation, and feature engineering to prepare data for machine learning and deep learning models.
- Fine-tune models through hyperparameter optimization (grid search, random search, Bayesian optimization) to improve performance metrics (accuracy, precision, recall, F1-score).
- Monitor model performance to address drift, overfitting, and bias.
Collaboration & Research :
Collaborate with cross-functional teams including data scientists, engineers, and product managers to integrate machine learning solutions into production. Stay up to date with the latest AI/ML trends and research, applying cutting-edge techniques to projects.
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