Create secure and high-quality production code, maintaining algorithms that run synchronously with systems
Produce architecture and design artifacts for complex applications, ensuring design constraints are met
Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets
Identify hidden problems and patterns in data to drive improvements in coding hygiene and system architecture
Contribute to software engineering communities of practice and events exploring new and emerging technologies
Required Qualifications, Capabilities, and Skills
Formal training or certification in software engineering concepts
Experience as a hands-on practitioner developing production AI/ML solutions
Familiarity with agentic workflows and frameworks such as LangChain, LangGraph, Auto-GPT
Deep knowledge and experience in machine learning and artificial intelligence
Expertise in at least one area: 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, and statistics
Understanding of machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn
Strong programming knowledge of Python and Spark; proficiency in vector operations using numpy, scipy; experience with distributed computation using multithreading, multi GPUs, Dask, Ray, Polars
Familiarity with AWS Cloud services such as EMR, Sagemaker
Overall knowledge of the Software Development Life Cycle
Solid understanding of agile methodologies including CI/CD, application resiliency, and security
Preferred Qualifications, Capabilities, and Skills
Exposure to cloud technologies
