We are seeking an AI Engineer with expertise in training machine learning models and a strong understanding of the toolchain. The ideal candidate will have hands-on experience in fine-tuning, optimizing, and deploying models, ensuring efficient training pipelines for real-world applications.
About the Role:
Location: Ahmedabad
Experience: 5+ years of total industry experience, with at least 2+ years in AI/ML model training.
Education preference: Bachelor’s degree in Computer Science, Engineering, or a related field.
Key Responsibilities:
- Rain and fine-tune ML/DL models for various AI applications (e.g., NLP, CV, or Predictive Analytics).
- Implement and optimize training pipelines, ensuring efficiency and scalability.
- Work with toolchains (e.g., TensorFlow, PyTorch, Hugging Face, ONNX, MLflow, Weights & Biases).
- Leverage data preprocessing, augmentation, and feature engineering techniques to improve model performance.
- Optimize models for deployment (quantization, pruning, distillation, etc.).
- Collaborate with Data Scientists, MLOps engineers, and software developers to integrate AI solutions into production systems.
- Stay updated with the latest AI research, open-source models, and best practices.
Required Skills & Qualifications:
- 5+ years of total industry experience, with at least 2+ years in AI/ML model training.
- Hands-on experience with AI training pipelines and frameworks (PyTorch, TensorFlow, JAX, etc.).
- Experience in model fine-tuning, hyperparameter optimization, and dataset curation.
- Strong programming skills in Python (NumPy, Pandas, Scikit-learn, etc.).
- Familiarity with GPU acceleration (CUDA, TensorRT) and cloud-based training (AWS, GCP, Azure).
- Experience with MLOps tools like MLflow, Weights & Biases, or Kubeflow is a plus.
- Solid understanding of deep learning architectures (CNNs, Transformers, LLMs, etc.).