Job Description

Job Requirements

Understands end to end objectives and develop models that help them to achieve them along with metrics to track their progress Analysing the ML algorithms that could be used to solve a given problem and ranking them by their success probability Work collaborate closely with cross-functional teams to deliver AI-driven products that reshape industries and user experiences Supervising the data acquisition process if more data is needed Contribute to creating AI-powered solutions that generate high-quality content, images, text, audio, or other media while pushing the boundaries of creativity and innovation. This role requires a deep understanding of machine learning, neural networks, and generative modeling techniques. Performance tuning Technical Documentation skills

Work Experience

Stay up-to-date with the latest advancements in generative AI, deep learning, and related fields. Contribute to the research and development of novel generative models, exploring new algorithms and methodologies

Model Architecture

: Design and develop custom generative models tailored to specific applications. Experiment with various neural network architectures

Data Processing

: Prepare and preprocess datasets to be used for training generative models. Apply techniques such as data augmentation, normalization, and transformation to ensure optimal model performance.

Training and Optimization

: Train generative models on large-scale datasets using appropriate frameworks and libraries. Optimize models for efficiency, speed, and quality of generated output.

Evaluation Metrics

: Develop and implement metrics to evaluate the quality, diversity, and novelty of generated content. Continuously iterate on models to improve these metrics.

Deployment

: Collaborate with Other Digital Teams to integrate generative models into production systems. Ensure scalability, reliability, and efficiency of the deployed models.

Collaboration

: Work closely with cross-functional teams to translate business requirements into generative AI solutions.

Documentation

: Document your research, experiments, and codebase thoroughly. Create clear and concise documentation for fellow engineers and stakeholders.

Continuous Learning

: Stay informed about industry trends and emerging technologies. Attend conferences, workshops, and seminars to maintain expertise in the field of generative AI.