AI Engineer

Model Training & Toolchain Expertise

About the Role:

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.

Key Responsibilities:

• Train 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.).

Why Join Us?

• Work on cutting-edge AI projects that impact real-world applications.
• Be part of a dynamic and collaborative AI team.
• Opportunity to innovate and experiment with the latest AI advancements.

Apply or connect with us to explore this opportunity.