Generative AI/Large Language Modelling Engineer

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Job Description - Generative AI/Large Language Modelling Engineer

Responsibilities

  • Designing, developing, and implementing generative AI models and algorithms utilizing state-of-the-art techniques such as GPT, VAE, and GANs.
  • Collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.
  • Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.
  • Developing and maintaining AI pipelines, including data preprocessing, feature extraction, model training, and evaluation
  • Optimizing existing generative AI models for improved performance, scalability, and efficiency.
  • Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.

Requirements

  • Master’s degree or higher in Computer Science, Engineering, or a related field.
  • Proven experience in machine learning and artificial intelligence development.
  • Proficiency in programming languages such as Python, R, or Java
  • Experience with natural language processing (NLP) and large language modelling (e.g., BERT, GPT-3, GPT-4)
  • Understanding of deep learning architectures and techniques.
  • Strong mathematical and statistical background.
  • Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn).
  • Excellent problem-solving and critical-thinking skills.
  • Ability to work independently and in a collaborative team environment.
  • Good communication and presentation skills.

Preferred Skills and Qualifications

  • Knowledge of distributed computing and big data technologies (e.g., Spark, Hadoop).
  • Previous work on real-world AI applications or projects.
  • Publications or contributions to the AI/ML community.

Benefits

  • Competitive remuneration package adjusted to proven skills and experience;
  • Excellent working conditions;
  • Exposure to training and professional development capabilities, including the ability to engage in cutting-edge research;
  • Exposure to international clients and collaborators.
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