Generative AI/Large Language Modelling Engineer
vor 1 Monat
- 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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