Senior AI/ML Engineer

Summary:

We are seeking a talented and motivated AI Engineer to join our team and focus on building cutting-edge Generative AI applications. The ideal candidate will possess a strong background in data science, machine learning, and deep learning, with specific experience in developing and fine-tuning Large Language Models (LLMs) and Small Language Models (SLMs). You should be comfortable managing the full lifecycle of AI projects, from initial design and data handling to deployment and production monitoring. A foundational understanding of software engineering principles is also required to collaborate effectively with engineering teams and ensure robust deployments.

Responsibilities:

• Design, develop, and implement Generative AI solutions, including applications leveraging Retrieval-Augmented Generation (RAG) techniques.
• Fine-tune existing Large Language Models (LLMs) and potentially develop smaller, specialized language models (SLMs) for specific tasks.
• Manage the end-to-end lifecycle of AI model development, including data curation, feature extraction, model training, validation, deployment, and monitoring.
• Research and experiment with state-of-the-art AI/ML/DL techniques to enhance model performance and capabilities.
• Build and maintain scalable production pipelines for AI models.
• Collaborate with data engineering and IT teams to define deployment roadmaps and integrate AI solutions into existing systems.
• Develop AI-powered tools to solve business problems, such as summarization, chatbots, recommendation systems, or code assistance.
• Stay updated with the latest advancements in Generative AI, machine learning, and deep learning.

Qualifications:

• Proven experience as a Data Scientist, Machine Learning Engineer, or AI Engineer with a focus on LLMs and Generative AI.
• Strong experience with Generative AI techniques and frameworks (e.g., RAG, Fine-tuning, Langchain, LlamaIndex, PEFT, LoRA).
• Solid foundation in machine learning (e.g., Regression, Classification, Clustering, XGBoost, SVM) and deep learning (e.g., ANN, LSTM, RNN, CNN) concepts and applications.
• Proficiency in Python and relevant libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
• Experience with data science principles, including statistics, hypothesis testing, and A/B testing.
• Experience deploying and managing models in production environments (e.g., using platforms like AWS, Databricks, MLFlow).
• Familiarity with data handling and processing tools (e.g., SQL, Spark/PySpark).
• Basic understanding of software engineering practices, including version control (Git) and containerization (Docker).
• Bachelor's or master’s degree in computer science, Artificial Intelligence, Data Science, or a related quantitative field.

Preferred Skills:

• Experience building RAG-based chatbots or similar applications.
• Experience developing custom SLMs.
• Experience with MLOps principles and tools (e.g., MLFlow, Airflow).
• Experience migrating ML workflows between cloud platforms.
• Familiarity with vector databases and indexing techniques.
• Experience with Python web frameworks (e.g., Django, Flask).
• Experience building and integrating APIs (e.g., RESTful APIs).
• Basic experience with front-end development or UI building for showcasing AI applications.

Qualifications

Bachelorʼs or Masterʼs degree in Computer Science, Engineering, or a related discipline.