Generative AI Engineer

Role: Generative AI Engineer
Location: Irving, TX
Job Type: Full-Time
Salary: $100,000 - $120,000/year


Role Summary
We are seeking an experienced Generative AI Engineer with strong expertise in Python, Machine Learning, NLP, Deep Learning, and Generative AI/LLMs . The ideal candidate will design and develop advanced AI solutions, work with open-source LLMs, prepare and analyze data, and implement scalable AI models for complex business problems.
Must-Have Technical Skills
Strong proficiency in Python and major ML/AI libraries.
Hands-on experience with Generative AI and open-source LLMs , such as Llama, Dolly , or similar models.
Strong understanding of:
Machine Learning
Natural Language Processing (NLP)
Deep Learning
Neural Networks
Transformers
Experience with Generative AI techniques , including:
Text Generation
GANs
Text-to-Image Generation
Generative Models
Strong experience with SQL, data wrangling, data cleaning, and feature engineering .
Experience with model training, evaluation, Eligible to workimization, and experimentation .
Good-to-Have Skills
Experience with AWS, Azure, or Eligible to workP .
Experience developing AI solutions across on-premises and cloud environments .
Knowledge of CI/CD and MLOps practices .
Experience with responsible AI, model bias evaluation, and AI governance.
Key Responsibilities
Design, develop, and implement advanced AI and Generative AI solutions for complex business problems.
Collaborate with engineers, researchers, data scientists, and product managers to translate business requirements into technical AI solutions.
Gather, clean, transform, and prepare data for AI model training and evaluation.
Develop and Eligible to workimize Machine Learning, NLP, Deep Learning, and Generative AI models .
Explore and implement state-of-the-art AI techniques, including transformers, LLMs, computer vision, and generative models .
Evaluate different model architectures, parameters, and techniques to improve performance.
Fine-tune and Eligible to workimize open-source LLMs where applicable.
Analyze model performance, identify potential biases, and support responsible AI development.
Build AI solutions that can be deployed across cloud and on-premises environments.
Work with engineering teams to integrate AI models into production applications.
Support CI/CD, model deployment, testing, monitoring, and continuous improvement.

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