AI/ML Engineer

We are seeking a AI/ML Engineer with approximately 5 years of experience in the field. The ideal candidate will have a strong foundation in traditional Machine Learning (ML) skills, data science, and advanced AI techniques. You will be working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and other state-of-the-art technologies. Additionally, familiarity with cloud operations will be beneficial. If you are passionate about pushing the boundaries of AI and enjoy working on complex challenges, we want to hear from you.

Responsibilities:

• Design, implement, and optimize traditional Machine Learning models and algorithms.
• Develop and maintain data pipelines, perform exploratory data analysis, and apply data preprocessing techniques to ensure high-quality input for Machine Learning models.
• LLM & RAG Implementation: Leverage and fine-tune Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems to enhance LLMs performance and create innovative solutions.
• Utilize and integrate modern tools and frameworks (e.g., TensorFlow, PyTorch, LangChain, LlamaIndex, and Hugging Face) to build advanced solutions and platforms.
• Manage and optimize Machine Learning workflows in cloud environments (e.g., Azure, AWS, GCP), ensuring scalability and efficiency.
• Work closely with cross-functional teams, including data engineers, data scientists, software engineers, and product managers, to align on project goals and deliver high-impact solutions.

Requirements:

• Approximately 5 years of professional experience in Machine Learning and AI engineering.
• Proficiency in Python and relevant libraries (e.g., NumPy, pandas, scikit-learn). Strong understanding of Machine Learning algorithms, statistical analysis, and model evaluation techniques.
• Hands-on experience with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) technologies, including fine-tuning and deployment.
• Solid background in Data Science principles, including data preprocessing, feature engineering, and model selection.
• Cloud Operations: Experience with cloud platforms (Azure, AWS, GCP) and knowledge of cloud-based Machine Learning services and deployment strategies.
• Familiarity with Machine Learning frameworks and tools (e.g., TensorFlow, PyTorch, Hugging Face Transformers) and version control systems (e.g., Git).
• Hands-on experience with Apache Spark and Databricks highly desirable.
• Strong analytical and problem-solving skills, with the ability to tackle complex challenges and derive actionable insights.
• Excellent communication skills, with the ability to present technical concepts clearly and effectively to non-technical stakeholders.
• Experience working in an Agile or iterative development environment is a plus.