Overview
As a Data Scientist, you will work on advanced AI / ML models, focusing on RAG, LLMs, prompt engineering, and AI Agents. You will collaborate with cross-functional teams to enhance AI capabilities, develop innovative solutions, and optimize machine learning models.
Being a part of the Engineering team, based in the US and Europe, this role will bring you great opportunities to work on various projects, technologies, with a diverse range of teams.
The Engineering team is responsible for the design, development, and deployment of the organization's core products, with a focus on efficiency and speed. We architect and implement comprehensive solutions, including tools and platforms, to address key business requirements. These solutions encompass critical areas such as provisioning, configuration, continuous integration / continuous delivery (CI / CD), monitoring, service level agreements (SLAs), performance optimization, and system uptime. The team is committed to meticulous execution and collaborates extensively with a broad range of stakeholders throughout the product lifecycle.
This is a fully remote role from Spain.
Responsibilities
- Develop, fine-tune, and optimize Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.
- Implement AI Agents capable of decision-making and interactive learning.
- Research and experiment with various prompt engineering techniques to improve model performance and accuracy.
- Build and maintain machine learning pipelines for AI / ML models in production environments.
- Work with structured and unstructured data, including text, images, and multimodal datasets.
- Collaborate with software engineers and data engineers to integrate AI models into scalable applications.
- Analyze and interpret model outputs to refine algorithms and improve performance.
- Stay updated on the latest AI and ML research and contribute to internal knowledge-sharing initiatives.
Qualifications
Required Qualifications :
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
- 1+ years of professional experience.
- Strong programming skills in Python and familiarity with libraries such as TensorFlow, PyTorch, LangChain, and Hugging Face Transformers.
- Experience with NLP, LLM fine-tuning, and retrieval-based systems.
- Knowledge of prompt engineering techniques, LLM jailbreak methods and AI Agents.
- Understanding of traditional and modern machine learning algorithms, including deep learning architectures.
- Familiarity with cloud platforms such as AWS, GCP, or Azure for AI / ML deployments.
- Basic understanding of data engineering, ETL pipelines, and model deployment.
Preferred Qualifications :
- Experience with RAG architectures, vector databases (FAISS, Pinecone), and embedding models.
- Hands-on experience with MLOps, model monitoring, and performance tuning.
- Exposure to reinforcement learning and generative AI models.
- Strong analytical and problem-solving skills with the ability to work in a fast-paced environment.
- Strong communication and presentation skills with the ability to explain technical concepts to non-technical audiences.
- Soft skills: Good collaboration skills at all levels with cross-functional teams.
- Highly developed ownership and creative thinking.
- Analytical thinking and the ability to solve complex problems; process orientation and ability to build effective solutions; time management and organizational skills; fluent English language skills.
Additional Information