Developing AI/ML algorithms to analyze huge volumes of historical data to make predictions and recommendations.
Implement and optimize deep learning models for generative tasks such as image synthesis, voice etc
Collaborate with software engineers to integrate Generative AI models into production systems
Should be able evaluate the application cases and problem-solving potential of AI/ML algorithms and rank them according to success likelihood.
Should be able to comprehend data through exploration and visualization, spot discrepancies in data distribution
Should be able to work on structured as well as unstructured data
Should be able to develop various algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in production
Should be able to leverage cloud platforms for training and deploying large scale solutions (AWS Preferred)
Should have working knowledge on managing ModelOps framework
Should understand CI/CD processes in product deployment and used it in delivery.
Should be able to collaborate with data engineers to build data and model pipelines and maintain accuracy
Should be able to take complete ownership of the assigned project
Experience of working in Agile environments
Well versed with JIRA or equivalent project tracking tool
Competencies / Skills
Understanding of AI/ML frameworks,LLM libraries, data structures, data modeling, and software architecture.
Proficiency with a deep learning framework such as TensorFlow, Keras, NLP and text analytics and ML algorithms like clustering, regression, classification etc
Proficiency with Python and basic libraries for machine learning such as scikit-learn, pandas
Experience working with recommendation engines, data pipelines and distributed machine learning
Ability to select hardware to run an ML model with the required latency
