Artificial Intelligence and Machine Learning Professional
1 day ago
At Arting Digital Private Limited, we are seeking a skilled Ai/ml Engineer to join our team. This is an exciting opportunity for experienced professionals to leverage their expertise in AI and machine learning to drive business growth and innovation.
About the Job
We are looking for a highly motivated and detail-oriented Ai/ml Engineer with a strong background in artificial intelligence and machine learning. The ideal candidate will have experience working with large datasets, developing and training machine learning models, and implementing them in production environments.
This role requires a deep understanding of machine learning algorithms, data preprocessing techniques, and model evaluation metrics. Strong programming skills in languages like Python, PyTorch, and TensorFlow are essential. Experience with distributed training, hyperparameter tuning, and model optimization is also desirable.
The successful candidate will be responsible for designing, developing, and deploying AI-powered solutions that drive business outcomes. They will work closely with cross-functional teams to understand business requirements and develop scalable, efficient, and effective AI-based solutions.
Job Responsibilities
- Data Collection, Preprocessing, and Management: Gather diverse datasets for training LLMs or other machine learning models. Clean and preprocess raw text data using tools such as SpaCy, NLTK, or custom preprocessing pipelines. Create synthetic data or perform augmentation techniques to enrich training datasets.
- Building and Training Machine Learning Models: Design and implement deep learning architectures for specific use cases (e.g., LLMs for NLP tasks like sentiment analysis, text summarization, question answering). Train large models like transformers using large-scale datasets. Fine-tune pre-trained models on task-specific data to improve performance on downstream applications.
- Model Optimization and Scaling: Experiment with hyperparameters to enhance model performance and prevent overfitting. Use model optimization techniques such as quantization, pruning, and knowledge distillation to reduce the size and improve the inference speed of large models. Implement distributed training using PyTorch Distributed or TensorFlow's MirroredStrategy to train large models efficiently across multiple GPUs/TPUs.
- Model Deployment and Integration: Deploy AI/ML models into production environments ensuring scalability, security, and robustness. Build APIs or microservices for serving models, enabling real-time predictions or batch processing using frameworks like Flask, FastAPI, or TensorFlow Serving. Monitor systems to track the performance and accuracy of models in production.
Requirements
- Python, PyTorch, LLM Models, TensorFlow
The salary for this position is approximately $140,000 per year, commensurate with experience.
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