What are the responsibilities and job description for the Software Development Engineer position at Convergenz?
Roles and Responsibilities :
Stay up to date on the most current developments in the generative AI space
Deploy machine learning models and services on cloud platforms such as AWS, Google Cloud, or Azure
Collaborate with cross-functional teams, including data scientists, researchers, and other engineers, to integrate LLMs and RAG into broader projects
Manage large datasets, including data cleaning, preprocessing, and transformation
Develop and maintain data pipelines to ensure seamless data flow for model training and evaluation
Communicate technical concepts and project progress to non-technical stakeholders and team members
Conduct experiments to fine-tune parameters and optimize model performance
Implement techniques to improve the efficiency and scalability of LLM and RAG systems
Stay up-to-date with the latest advancements in NLP, machine learning, and deep learning fields to inform project strategies
Monitor and maintain deployed models to ensure they perform reliably and meet performance benchmarks
Ensure code quality by following best practices in software development, including version control, testing, and continuous integration / continuous deployment (CI / CD)
Document code and maintain comprehensive technical documentation to support team knowledge sharing and project handovers
Requirements :
10 years of experience delivering production ready , industrial strength code, and implementing CI / CD pipelines.
Proficiency in Python and familiarity with libraries such as TensorFlow and PyTorch.
Extensive experience with neural network architectures, particularly transformers, and NLP techniques.
RAG and Data Engineering : - Understanding of Retrieval-Augmented Generation (RAG) and hands-on experience with implementing RAG solutions.
Proficiency in handling and preprocessing large datasets, as well as experience with data pipelining and ETL processes.
Experience with cloud platforms like AWS, Google Cloud, or Azure for deploying ML models.
Strong software engineering fundamentals, including version control, testing, and CI / CD.
Ability to design efficient algorithms for data retrieval and model training, and optimize models through Hands-on experience with the following
Python, pytorch, tensofflow, pandas, Scikit-learn, teras and other AI / Ml libraries - JavaScript - Other object-oriented programming languages - React.js - Cloud Architecture Frameworks such as AWS well architected
Experience with Large Language Models (LLM) and Retrieval-Augmented Generation (RAG) architecture
Hands-on senior software developer with real-life experience designing, developing, and deploying large language models (LLMs) and Retrieval-Augmented Generation (RAG) solutions to production environments.
Not looking for someone that only has theoretical or white / board design experience
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Washington, DC
Full Time