Contributes to software engineering communities of practice and events that explore new and emerging technologies
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 3+ years applied experience
Experience as a hands-on practitioner developing production AI/ML solutions.
Familiarity with agentic workflows and relevant frameworks, such as LangChain, LangGraph, Auto-GPT etc.
Deep knowledge and experience in machine learning and artificial intelligence.
Expert in at least one of the following areas: Large Language Models, Natural Language Processing, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.
Knowledge of Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics.
Demonstrated understanding in machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn.
Strong programming knowledge of python, spark; Strong grasp on vector operations using numpy, scipy; Strong grasp on distributed computation using Multithreading, Multi GPUs, Dask, Ray, Polars etc.
Familiarity in AWS Cloud services such as EMR, Sagemaker etc.,
Overall knowledge of the Software Development Life Cycle
Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
Exposure to cloud technologies