YOUR TASKS
• Collaborate with AI engineers and researchers to design, develop, and test machine learning and deep learning models.
• Train and fine-tune deep learning models using real-world datasets tailored to specific use cases.
• Contribute to the extension and optimization of our existing AI/ML infrastructure, including model training pipelines, evaluation tools, and deployment workflows.
• Fine-tune and adapt Large Language Models (LLMs) and/or Vision-Language Models (VLMs) using domain-specific or customer-provided datasets.
• Leverage the capabilities of LLMs/VLMs to build intelligent solutions that address diverse customer challenges, from natural language understanding to visual recognition tasks.
• Engage in experimentation and research, exploring new techniques to enhance model performance and efficiency.
• Document your work, communicate technical findings clearly, and contribute to internal knowledge sharing.
YOUR PROFILE
• Currently enrolled in a Bachelor’s or Master’s degree program in Computer Science, Artificial Intelligence, Data Science, or a related field with a strong focus on AI/ML.
• Solid foundation and hands-on experience with Python programming language and proficient in scientific computing libraries such as NumPy.
• Strong understanding of Image Processing and Computer Vision concepts and experience using libraries such as OpenCV and Matplotlib.
• Familiarity with core concepts of Machine Learning, including data preprocessing, model training, and evaluation. Practical experience with ML libraries such as Scikit-learn.
• Knowledge of Deep Learning and Deep Learning architectures, such as: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformers, etc. Experience with PyTorch.
• Familiarity with Large Language Models (LLMs) and Vision Language Models (VLMs) and their applications.
• Strong verbal and written communication skills in English.
HELPFUL ADDITIONAL QUALIFICATIONS
Nice to have:
• Experience with C/C++ programming, preferably in performance-critical applications.
• Familiarity with advanced vision frameworks such as: Detectron2 and MMDetection.
• Hands-on experience with the Hugging Face Transformers library.
• Knowledge of Agentic AI systems and autonomous agents.
• Experience working with LangChain and building LLM-based pipelines or applications.
• Experience with fine-tuning LLMs and VLMs.
• Experience with Amazon Web Services (AWS).
• Experience with Web services.
• Experience with Flask and FastAPI.
• Experience with Docker.
• Experience with MLOps and LLMOps.
