What are the responsibilities and job description for the Sr. GenAI Developer position at InfoVision Inc.?
Hello,
We have an immediate Openings with Our Direct Client for a Long-term contract position
Job Title: Sr. GenAI Developer
Location: Irving TX, Columbus Ohio / Atlanta GA
GenAI (6 Months)
Expertise in providing run support for applications and products.
Experience with GenAI technologies like CoPilot and Codeium is preferred.
Be able to quickly fix the problems for end users
Knowledge of the data and underlying architecture to facilitate the application of GenAI at Verizon
Be able to work on unique projects to create and incorporate GenAI technology to improve developer capabilities and experience
Technical Expertise
Strong understanding of Generative AI tools: Hands-on experience with GitHub Copilot, self-hosted generative AI platforms, or similar tools, including installation, configuration, and maintenance.
Programming expertise: Proficiency in programming languages such as Python, JavaScript, or other languages commonly used with AI/ML tools.
Containerization and orchestration: Experience with Docker and Google Kubernetes Engine for deploying and managing self-hosted generative AI tools.
Cloud platforms: Familiarity with AWS and GCP to support hosting and scaling AI products in cloud environments.
Operational Expertise
Monitoring and troubleshooting: Proven experience in monitoring AI systems for performance, identifying bottlenecks, and troubleshooting issues to maintain high availability.
Optimization: Ability to fine-tune generative AI models or systems for improved performance, latency reduction, and user experience.
Generative AI-Specific Knowledge
Prompt engineering: Understanding of prompt design, token optimization, and use case adaptation for generative AI tools.
Model usage insights: Ability to analyze usage metrics (e.g., token consumption, accuracy, and failure rates) and derive insights for improving user adoption and efficiency.
Self-hosted model operations: Experience managing fine-tuning, updating, or upgrading models hosted on proprietary infrastructure.
Knowledge of ML frameworks: Familiarity with frameworks such as TensorFlow, PyTorch, or Hugging Face for working with custom AI models if required.
Preferred Qualifications
Experience with large language models (LLMs) like OpenAI GPT, Anthropic, or similar tools.
Exposure to enterprise-scale generative AI deployments.
Certifications in AI/ML or cloud platforms (e.g., AWS Certified Machine Learning, Google Cloud AI Engineer).
Familiarity with DevOps principles to improve the deployment and monitoring lifecycle of generative AI tools.
If interested, Please share below details with update resume:
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