Gen AI Engineer

Job Description:

• Collect, curate, and prepare data to train and evaluate multimodal foundation models. Responsibilities may include cleaning and transforming text data or generating synthetic datasets.
• Design, build, and optimize large-scale generative models such as GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders).
• Contribute to projects covering language modeling, text generation, language understanding, and contextual comprehension.
• Continuously assess and fine-tune Large Language models to deliver the highest accuracy and relevance for tailored datasets.
• Develop and deploy AI applications on cloud infrastructure across any hyperscaler, including Azure, GCP, or AWS.
• Connect AI models with the company’s data to improve, enhance, and augment existing applications.

Role & Responsibility

• Manage data preprocessing, augmentation, and the creation of synthetic data.
• Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution).
• Develop and maintain AI pipelines.
• Work with custom datasets, applying techniques such as chunking and embeddings to train and fine-tune models.
• Integrate Azure cognitive services (or comparable platform services) to expand functionality and improve AI solutions.
• Partner with cross-functional teams to ensure efficient deployment and seamless integration of AI solutions.
• Ensure AI systems are robust, efficient, and scalable.
• Keep current with the latest developments in AI and machine learning technologies.

Skills & Experience

· Strong understanding of machine learning, deep learning, and computer science.

· Expertise in generative AI models and methodologies (e.g., GANs, VAEs, Transformers).

· Experience with natural language processing (NLP) and computer vision is a plus.

· Ability to work effectively both independently and in a team environment.

· Knowledge of advanced programming with a focus on Python, along with AI-centric libraries including TensorFlow, PyTorch, and Keras. This includes the capability to implement and work with complex algorithms that are core to building generative AI models.

· Knowledge of natural language processing (NLP) for text generation tasks such as text parsing, sentiment analysis, and using transformer-based models like GPT (generative pre-trained transformer) models.

· Experience with data management, including data preprocessing, augmentation, and synthetic data generation. Responsibilities include cleaning, labeling, and augmenting data to train and enhance AI models.

· Experience building and deploying AI models in production environments.

• Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker, along with orchestration tools such as Kubernetes, for deploying, managing, and scaling AI solutions
• Should be able to bring new ideas and innovative solutions to our clients