GEN AI with ML Engineer

Overview

On Site
$60,000 - $80,000
Full Time

Skills

Machine Learning & Deep Learning
Generative Models
Python & TensorFlow
Data Science
Prompt Engineering
Fine-tuning
MLOps
AI Application Development

Job Details

Specific Skills and Concepts:
  • Machine Learning and Deep Learning Fundamentals:
    A foundational understanding of how machine learning models learn from data is essential for understanding generative AI. Deep learning, particularly neural networks, is often the core technology behind generative models.
  • Generative Models:
    Knowledge of different generative model types, such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformers, is crucial for creating various types of content.
  • Programming Languages and Libraries:
    Python is the dominant language for AI development, and proficiency in libraries like TensorFlow and PyTorch is essential for building and training generative models.
  • Data Science:
    Skills in data manipulation, cleaning, and analysis are important for preparing data to train generative models.
  • Prompt Engineering:
    Crafting effective prompts to guide generative models in producing desired outputs is a critical skill.
  • Fine-tuning:
    The ability to adjust pre-trained models to specific tasks or datasets is important for optimizing performance.
  • MLOps:
    Machine Learning Operations (MLOps) skills are essential for deploying, monitoring, and maintaining generative AI models in production.
  • AI Application Development:
    Skills in integrating AI functionalities into applications, including web applications, are valuable for practical use.
  • Understanding AI Limitations:
    It's important to understand the potential biases and limitations of generative AI models to use them responsibly.
  • Human-Machine Collaboration:
    Generative AI is often used to augment human capabilities, so understanding how to work with AI as a collaborator is essential.
  • Cybersecurity Awareness:
    With the rise of generative AI, understanding potential security risks and vulnerabilities is crucial.
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