Current Openings AI / Gen AI Developer

Job Description

Come join the eG Innovations family. Do what you love. AI / Gen AI Developer We are looking for a technically skilled Candidate to join our team as an AI / Gen AI Developer. This role involves developing applications powered by large language models (LLMs) and advanced AI techniques, utilizing tools like ChatGPT and Gemini to drive innovation. The ideal candidate will have a strong foundation in AI concepts, proficiency in Java, familiarity with Lang Chain for LLM applications, and knowledge of containerization and model deployment. Roles Responsibilities: AI Model and LLM Application Development: Design, develop, and fine-tune AI and LLM applications using GenAI models and frameworks. Algorithm Implementation: Build and implement AI algorithms using Java and Python, integrating machine learning models into applications. Data Processing Analysis: Collect, preprocess, and analyse data to support high-quality model training and application development. Model Integration and Deployment: Implement and deploy models in backend systems, ensuring smooth integration and operation of AI solutions. Performance Optimization: Optimize AI/LLM applications for efficiency, responsiveness, and scalability. Documentation : Maintain comprehensive documentation for models, algorithms, and development processes for efficient collaboration and future scalability. Technical Skills Required: Core AI and Machine Learning: AI Fundamentals: Understanding of supervised, unsupervised, and reinforcement learning methods, including foundational AI principles. Machine Learning Algorithms: Knowledge of common algorithms (e.g., decision trees, clustering, regression models). Large Language Models (LLMs): Experience with transformer models (e.g., GPT, BERT) and familiarity with LLM deployment. Deep Learning Frameworks: TensorFlow or PyTorch: Basic experience with deep learning frameworks to build and fine-tune neural networks. Natural Language Processing (NLP): Proficiency in NLP techniques, including tokenization, text preprocessing, embeddings, and generative text. Lang Chain Framework: Knowledge of Lang Chain for creating and managing LLM-based applications. Programming Skills: Java: Proficiency in Java for backend logic, integration, and AI algorithm implementation. Python: Basic skills in Python, especially with libraries like NumPy, pandas, and scikit-learn for data manipulation and machine learning. Data Management Processing: Data Preprocessing: Experience in data preprocessing, cleaning, and transformation. SQL: Basic knowledge of SQL for database operations and data management. Optional Frontend Skills: JavaScript, HTML, CSS: Basic knowledge of frontend technologies for application integration and UI support. React.js or Angular: Familiarity with frontend frameworks (optional). Model Deployment and Optimization: Model Deployment: Experience with deployment tools and frameworks (e.g., TensorFlow Serving, Flask, Docker). Performance Tuning: Familiarity with model tuning techniques to optimize runtime performance and accuracy. Tools and Version Control: Git: Proficiency in version control with Git. Jupyter Notebooks: Experience with Jupyter for data exploration and prototyping.