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Job Title: Senior GenAI Developer
Locations: Irving, TX (Hybrid)
Duration: Long Term
Need Independent Resources
Description:
Responsibilities
•Design, development, and deployment of generative AI models and solutions.
•Collaborate with cross-functional teams to identify and prioritize AI-driven opportunities.
•Provide expertise in AI model training, fine-tuning, and optimization.
•Fine tune open source models and/or build telecom specific Generative AI models
•Develop and implement best practices for AI model development and deployment.
•Stay up-to-date with the latest advancements in generative AI and related fields and make recommendations for improvements
•Mentor and guide junior team members in AI-related projects.
•Ensure AI solutions meet business requirements and performance standards.
•Conduct research and experiments to explore new AI techniques and methodologies.
•Communicate complex AI concepts to non-technical stakeholders effectively.
•Collaborate with cross-disciplinary teams – developers, other data scientist, data analysts, business
•Monitor and correlate inputs and outputs, establish meaningful metrics
•Lead and act as a technical liaison between business, executives and data science teams to deliver POC’s / pilot on need basis.
Requirements
•Master’s degree in Data science, Computer Science, Artificial Intelligence, Machine Learning, or a related field
•Experience in data science , with a focus on generative AI technology/data science
•5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python)
•Telecommunication domain experience
•Ability to work independently and as part of a team in a fast-paced environment
•Hands on fine tuning AI models (SBERT, ScaNN, PaLM, ChatGPT, LLM)
•Strong background in Natural Language Processing, including experience with text representation, language modelling, sequence-to-sequence architectures, and semantic understanding
•Technical skills : Data science, Python, Javascript, MongoDB, AWS/GCP, API Programming, vertex.ai
•Strong expertise in generative AI techniques, including but not limited to:
o Generative Adversarial Networks (GANs)
o Variational Autoencoders (VAEs)
o Transformer models (e.g., GPT-3, GPT-4)
o Diffusion Models
•Proficiency in machine learning frameworks and libraries such as TensorFlow, PyTorch, Keras, etc.
•Solid understanding of deep learning concepts and neural network architectures.
•Experience with large-scale model training and optimization.
•Familiarity with natural language processing (NLP) and computer vision applications.
Programming and Tools:
o Proficiency in programming languages such as Python, R, or Java.
o Experience with data processing and analysis using tools like Pandas, NumPy, and scikit-learn.
o Knowledge of cloud platforms and services (e.g., AWS, Google Cloud, Azure) for AI model deployment.
o Experience with version control systems (e.g., Git).
•Strong analytical and problem-solving skills with the ability to develop creative and efficient solutions.
•Ability to work with large datasets and perform data preprocessing, augmentation, and transformation.
•Excellent written and verbal communication skills.
Preferred Qualifications:
•Publications or contributions to the AI community through research papers, open-source projects, or conference presentations.
•Experience with AI ethics and responsible AI practices.
•Familiarity with MLOps and continuous integration/continuous deployment (CI/CD) for AI projects.
