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1 Flexsin Technologies AI Engineer Job
Generative AI Engineer
Flexsin Technologies
posted 4mon ago
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Job Description
- Develop and fine-tune generative models using techniques like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Transformers, Diffusion models, etc.
- Work on tasks such as text generation, image generation, music or sound generation, video creation, and other creative AI applications.
- Design, build, and deploy models using frameworks like TensorFlow, PyTorch, Hugging Face, OpenAIs GPT, or similar tools.
- Optimize AI models for performance, accuracy, and scalability in real-world production environments.
- Research and stay updated on the latest trends, papers, and breakthroughs in generative AI.
- Collaborate with other teams (data scientists, machine learning engineers, product teams) to integrate models into production systems.
- Work on data preprocessing, augmentation, and designing pipelines to ensure high-quality input for model training.
- Document your code, process, and model outputs for team-wide visibility and knowledge sharing.
- Bachelors or Masters degree in Computer Science or related fields.
- 3-4 years of hands-on experience in developing Generative AI solutions
- Strong understanding of deep learning algorithms, especially in generative models like GANs, VAEs, Diffusion models, or large-scale language models like GPT.
- Hands-on experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or Hugging Face.
- Experience working with neural networks, unsupervised learning, and natural language processing (NLP).
- Strong programming skills in Python, including deep learning libraries (e.g., TensorFlow, Keras, PyTorch).
- Familiarity with cloud platforms (AWS, GCP, or Azure) for model training and deployment.
- Strong mathematical and statistical knowledge, particularly in probability theory, linear algebra, and optimization.
- Experience in large-scale model training, fine-tuning, or distributed computing.
- Knowledge of reinforcement learning (RL) and self-supervised learning.
- Familiarity with AI ethics, bias mitigation, and interpretability in generative models.
Employment Type: Full Time, Permanent
Functional Areas: Analytics & Business Intelligence
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