- LLM Development: Design, develop, and optimize large language models, NLP systems, frameworks, and tools for both front-end and back-end development.
- Prototyping and Proof of Concepts (PoC): Create prototypes and conduct proof of concepts in LLM, NLP, Deep Learning (DL), Machine Learning (ML), object detection/classification, tracking, etc.
- Stay Up-to-Date: Keep abreast of the latest advancements in LLM, NLP, deep learning, machine learning, and object detection algorithms. Identify opportunities to leverage new technologies for improved solutions.
- Translation of Functional Requirements: Work with business users to translate functional requirements into data specifications.
- Collaboration: Collaborate with researchers, engineers, data scientists, and business users to transform domain knowledge into functional requirements.
- Model Training and Evaluation: Train and fine-tune language models using appropriate machine-learning frameworks and tools.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Proven experience as a Data Engineer with a focus on AI Language Models.
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
- Strong programming skills, particularly in Python, and experience with AI frameworks such as Llama Index, LangChain, TensorFlow, PyTorch, Keras, or Hugging Face.
- Familiarity with cloud platforms (e.g., Kubernetes, AWS, Azure, GCP) and related services is a plus.
- Proficiency with Docker, Kubernetes, Airflow, Kubeflow, MLOps, and DataOps principles.
- Collect and pre-process large-scale text corpora for training and fine-tuning language models. Conduct data analysis to identify patterns, trends, and insights.
- Utilize off-the-shelf LLM services, such as Cloud Open AI, to integrate LLM capabilities into applications. Collaborate with the research team to design and develop state-of-the-art language models.
Nice to Have:
- Solid understanding of ML/DL techniques, algorithms, and tools (e.g., CNN, RNN, Transformers).
- Hands-on experience with conversational AI technologies, including Natural Language Understanding, Generation, Dialog systems, Information retrieval, Question and Answering, and Machine Translation.
- Experience in training BERT, GPT, and Megatron Models using PyTorch.
- Understanding of MLOps life cycle, experience with MLOps workflows, traceability, versioning of datasets, and knowledge of database management and queries (SQL, MongoDB, etc.).
- Experience with end-to-end MLOps platforms such as Kubeflow, MLFlow, Airflow, Vertex AI.
If you are passionate about shaping the future of AI and data engineering, we invite you to join our team at Deutsche Telekom IT Solutions Hungary. Apply now and contribute to our exciting journey in the world of artificial intelligence.
* Please be informed that our remote working possibility is only available within Hungary due to European taxation regulation.
