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Generative Ai Training Jobs in Texas (NOW HIRING)

Stackruit Ltd.

Generative AI Engineer

Dallas, TX · On-site

$100 - $130/hr

Work on various project phases, from ideation to deployment, across generative AI and traditional ... Competitive salary, benefits package, and training opportunities. * Be part of a team that values ...

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Cognizant

Generative AI Lead Engineer

Dallas, TX · On-site

$120 - $140/hr

About the role As a Generative AI Engineer , you will make an impact by designing and building ... Experience with model training, fine-tuning, and optimization for performance, scalability, and ...

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Generative Ai Training information

What are some common challenges faced by professionals working in generative AI training roles?

Professionals in Generative AI training often encounter challenges such as ensuring data quality and diversity, combating model bias, and staying updated with fast-evolving algorithms. Collaborating closely with data scientists, engineers, and subject matter experts is essential to create robust training datasets and refine model outputs. Additionally, balancing computational resource demands with project deadlines can be demanding, making strong project management and adaptability key assets in this role.

What are the key skills and qualifications needed to thrive in generative AI training?

To thrive in Generative AI Training, you need a strong background in machine learning, data science, and programming (especially Python), often supported by a degree in computer science or a related field. Experience with frameworks like TensorFlow, PyTorch, and familiarity with large language models and cloud platforms is typically required. Strong analytical thinking, creativity, and effective communication are essential soft skills for designing training data and refining model outputs. These skills and qualities are crucial for developing high-quality, ethical, and scalable AI systems that meet organizational goals.

What is the difference between Generative Ai Training vs Data Scientist?

AspectGenerative Ai TrainingData Scientist
Required CredentialsKnowledge of AI models, programming, machine learningStatistics, programming, data analysis
Work EnvironmentAI development teams, tech companies, research labsBusiness, finance, tech firms, research institutions
Industry UsageDeveloping generative models like GPT, DALL·EData analysis, predictive modeling, insights generation

Generative Ai Training focuses on developing and fine-tuning AI models that generate content, requiring expertise in AI frameworks and machine learning. Data Scientists analyze data to extract insights and build predictive models. While both roles involve programming and data skills, Generative Ai Training is specialized in AI model creation, whereas Data Scientists work broadly with data analysis across industries.

What is generative AI training?

Generative AI training refers to the process of teaching artificial intelligence models, such as neural networks, to create new content like text, images, audio, or code. This is done by exposing the AI to large datasets so it can learn underlying patterns and generate outputs that mimic human-like creativity. The training process often involves techniques like supervised learning, unsupervised learning, or reinforcement learning, depending on the desired outcome. Generative AI is widely used in applications like chatbots, image generation, and content creation.
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Generative Ai Training jobs near you
Infographic showing various Generative Ai Training job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution.

Generative AI Engineer

Long Finch Technologies

Irving, TX • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Job Description

We are seeking a skilled Generative AI Engineer to design, develop, and deploy advanced AI solutions that solve complex business challenges. The ideal candidate will have strong expertise in Python, Large Language Models (LLMs), machine learning, deep learning, and Natural Language Processing (NLP), with hands-on experience building and optimizing generative AI applications using open-source models and modern AI frameworks.

Roles and Responsibilities

  • Design, develop, and implement advanced AI and Generative AI solutions to address complex business requirements.

  • Collaborate with engineers, researchers, product managers, and business stakeholders to translate business needs into scalable AI solutions.

  • Collect, clean, prepare, and engineer data for training, fine-tuning, and evaluating AI models while ensuring data quality and integrity.

  • Develop and optimize machine learning, deep learning, and NLP models for enterprise applications.

  • Build and deploy Generative AI solutions using Large Language Models (LLMs), text generation, and text-to-image generation techniques.

  • Evaluate, compare, and optimize AI model architectures, hyperparameters, and performance metrics.

  • Apply responsible AI practices by identifying model bias, improving fairness, and ensuring ethical AI development.

  • Develop scalable AI solutions that integrate with enterprise applications and cloud platforms.

  • Participate in model testing, deployment, monitoring, and continuous improvement.

  • Contribute to AI best practices, technical documentation, and knowledge sharing across teams.

Required Skills

  • Strong proficiency in Python with major machine learning and deep learning libraries.

  • Hands-on experience with open-source Large Language Models (LLMs) such as Llama, Dolly, or similar models.

  • Strong knowledge of Machine Learning, Deep Learning, Natural Language Processing (NLP), neural networks, transformers, supervised and unsupervised learning.

  • Experience with Generative AI techniques including text generation, text-to-image generation, and Generative Adversarial Networks (GANs).

  • Experience with data preprocessing, feature engineering, SQL, and data manipulation.

  • Familiarity with AI model evaluation, optimization, and hyperparameter tuning.

  • Strong analytical, problem-solving, and communication skills.

Preferred Skills

  • Experience with cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform (Google Cloud Platform).

  • Experience developing AI applications in both on-premises and cloud environments.

  • Knowledge of CI/CD pipelines and AI application deployment practices.

  • Familiarity with MLOps, model lifecycle management, and scalable AI deployment architectures.

Qualifications

  • Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

  • Experience designing, developing, and deploying enterprise AI or Generative AI solutions.

  • Ability to work effectively in cross-functional teams and deliver high-quality AI solutions in an agile environment.

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