Description :

Job Title : AI Architect

Job Summary :

We are looking for an innovative AI Architect to join our team and work on cutting-edge machine learning and artificial intelligence projects.

The ideal candidate will have experience in building, deploying, and optimizing AI/ML models, along with a strong foundation in data science, programming, and algorithms.

You will help drive the development of intelligent systems that leverage machine learning to solve real-world problems and improve business outcomes.

Key Responsibilities :

- Data Preparation and Analysis: Ability to understand large datasets, preprocess them, and extract features.

- Data Preprocessing Techniques: Knowledge of normalization, feature encoding, and handling missing values.

- Data Cleaning: Identifying and rectifying errors, outliers, and missing values within datasets.

- Design, develop, and implement machine learning & Deep Learning (FNN, CNN, RNN) models, with a focus on LLMs, generative AI, and fraud detection systems.

- Deploy and maintain ML models in AWS or any other cloud environments.

- Optimize model performance and scalability.

- Collaborate with cross-functional teams to integrate AI solutions into existing applications.

- Develop and maintain APIs (RESTful) for AI model integration.

- Implement MLOps best practices to streamline the ML lifecycle.

- Stay up-to-date with the latest advancements in AI/ML and incorporate new techniques into our workflow.

- Develop and implement fraud detection models to identify and prevent fraudulent activities.

- Evaluate model performance using appropriate metrics and techniques, ensuring high accuracy and reliability.

- Experience with Machine Learning Libraries and Frameworks: Familiarity with tools like TensorFlow, PyTorch, and scikit-learn, Keras.

GenAI Developer Job Description :

- We are seeking a talented Generative AI Developer to join our innovative team.

- The ideal candidate will have a strong background in AI and machine learning, with a focus on generative models and large language models (LLMs).

- You will work closely with cross-functional teams to conceptualize, design, test, and deploy AI projects that drive innovation and provide value in the rapidly evolving field of artificial intelligence.

- Join us and be part of a dynamic team that is shaping the future of AI.

- Advanced Programming Knowledge : Mastery in programming languages like Python and expertise in AI-specific libraries such as TensorFlow, PyTorch, and Keras.

- Proficiency in implementing and manipulating complex algorithms essential for generative AI development.

- Generative Models Expertise : In-depth experience with Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).

- Ability to design, train, and optimize these models for generating high-quality and creative content.

- Natural Language Processing (NLP) : Strong background in text generation techniques, including text parsing, sentiment analysis, and the use of transformers like GPT models for advanced text-based applications.

- Vector Databases : Hands-on experience with vector databases such as Pinecone, PgVector, and Qdrant for efficient retrieval and similarity search.

- Embedding, Retrieval-Augmented Generation (RAG), and Indexing : Expertise in creating embeddings, implementing RAG workflows, and indexing vector databases to improve search, retrieval, and contextual generation.

- LangChain and LangGraph: Expertise in building advanced workflows and applications using LangChain for LLM-based solutions and LangGraph for structured workflows with conditional logic.

- FastAPI and Microservices: Proficiency in building scalable, RESTful FastAPI applications and microservices architectures for deploying AI solutions.

- LangSmith and LangFuse: Experience using LangSmith for debugging and evaluation of LLM chains, and LangFuse for logging and analytics in LLM applications.

- Cloud Computing and Deployment: Expertise in deploying and managing AI applications on cloud platforms such as AWS, Google Cloud, and Microsoft Azure.

- Familiarity with Docker for containerization and Kubernetes for scaling and orchestration.