Artificial Intelligence Engineer - Data Modeling

Key Responsibilities :

- AI/ML Model Development : Design, develop, and deploy machine learning or large language (LLM) models

- Strong Analytical Skills : Apply your analytical expertise to extract actionable insights from complex datasets and leverage AI to address real-world problems.

- Data Analysis and Preprocessing : Handle data collection, cleaning, preprocessing, and exploratory data analysis to ensure data readiness and quality for modeling.

- Model Evaluation and Validation : Assess model performance using relevant metrics and validate outcomes through comprehensive testing.

- Collaboration : Work collaboratively with cross-functional teams, including data engineers, software developers, and domain experts, to understand requirements and deliver impactful solutions.

- Healthcare Domain Knowledge (Optional) : While not mandatory, a background in healthcare, medical imaging, or related fields is a valuable asset.

Technical Skills :

- Programming Skills : Proficiency in Python, with experience in AI/ML frameworks such as TensorFlow, PyTorch, and Hugging Face. Familiarity with TensorRT and NVIDIA Triton Server is a plus.

- Model Expertise : Deep experience with Convolutional Neural Networks (CNNs), diffusion models, transformers, as well as segmentation, object detection, and classification models, including CLIP or similar models.

- Multimodal Proficiency : Strong knowledge and experience with large language models (LLMs) and multimodal AI approaches.

- Algorithmic Understanding : Comprehensive understanding of a wide array of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning techniques.

Experience & Qualifications :

- Work Experience : At least 4+ years of proven experience as an AI researcher/engineer or in a

data science role

- Education : Bachelors degree in Computer Science, Engineering, or a related field (or equivalent work experience).