LLM Engineer

hace 4 semanas

Madrid, Madrid, España TD SYNNEX A tiempo completo
About the Role

We're seeking a highly skilled LLM Engineer to join our dynamic AI team at TD SYNNEX. As an LLM Engineer, you will play a key role in developing cutting-edge Gen AI solutions that leverage natural language processing, logic programming, and machine learning techniques to address complex business challenges.

Key Responsibilities
  • Design and implement AI algorithms and models for various applications, with a focus on Generative AI, NLP, logic programming, and machine learning.
  • Design, develop, and optimize RAG models to accurately retrieve information, utilizing vector databases and advanced indexing techniques to store and retrieve relevant information.
  • Prompt Engineering: Optimize LLM responses for different applications and use cases.
  • Python API Development: API calls and integrations with LLMs.
  • LLM Evaluation: Evaluate LLM performance.
  • Model Serving: Implement and manage LLM model serving infrastructure to provide scalable and reliable access for end users.
  • Fine-Tuning Models: Fine-tune pre-trained LLMs to enhance performance on specific tasks and use cases.
  • Internal Integrations: Develop and maintain integrations of LLM solutions with internal tools and systems to streamline workflows and enhance functionality.
  • Data Handling: Leverage deep Python knowledge to efficiently process and manage vast amounts of data for model training and evaluation.
  • Collaboration: Work closely with data scientists, software engineers, and product teams to integrate LLM capabilities into products and services.
  • Documentation: Create and maintain comprehensive documentation for developed models, systems, APIs, and integration processes as well as related best practices.
Requirements
  • Strong background in artificial intelligence (ML and NLP) processing and data analysis.
  • Proficiency in Python, Java, or C++ with preference for Python.
  • Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and NLP libraries (e.g., NLTK, SpaCy).
  • Hands-on experience with deploying LLMs and multimodal LLMs such as GPT-4.
  • Strong experience with data preprocessing, fine-tuning, model training.
  • Proficient with model evaluation techniques to determine which technique is best for which use case.
What We Offer

We provide competitive compensation with annual salary reviews.

Fully remote in Europe or hybrid work in Barcelona, Madrid, Lisbon.

We value continuous learning and provide a clear progression plan.

We provide comprehensive benefits including health insurance, paid leave, retirement plans, and more.

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