AI Research Engineer

hace 3 días


Barcelona, España Visium A tiempo completo

At Visium, we enable enterprise executives in defining their AI & Data strategy, execute large scale transformations and implement AI across operations, ensuring their organization becomes future-proof. We are building the Agentic AI Platform for Life Sciences companies - enabling pharma, biotech, and CROs to transform high-value workflows such as clinical trial documentation, regulatory submission writing, compliant marketing, and literature research. You will collaborate closely with researchers and engineers to implement and optimize systems that support the development and deployment of state-of-the-art AI solutions. This role is ideal for individuals who thrive at the intersection of research and engineering, particularly in building robust tooling and data pipelines for large-scale AI models such as LLMs. Data Engineering: Build and maintain robust data pipelines that handle diverse and large-scale datasets, ensuring data quality and accessibility for model training. Collaboration: Work closely with cross-functional teams, including data scientists, ML engineers, and product managers, to integrate AI solutions into real-world applications. Research Support: Support Data Science needs, run large-scale model training, and analyze results to support ongoing research initiatives. Tooling and Automation: Develop tools and automation scripts to streamline workflows, improve efficiency, and ensure reproducibility in research and development processes. Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proficiency in Python. Solid understanding of machine learning concepts and experience working with ML frameworks like TensorFlow, PyTorch, or JAX. Experience with large language models (LLMs) and understanding of their training and deployment challenges. Familiarity with MLOps practices and tools for continuous integration and deployment of ML models. Experience in deploying distributed systems, cloud computing platforms (e.g., AWS, GCP, Azure), and containerization technologies (e.g., Docker, Kubernetes). Strong skills in data processing, ETL pipelines, and working with large-scale datasets. A yearly education budget to steep your learning curve A yearly sport budget because a fit body leads to a fit mind A flexible working culture because your work-life balance matters to us


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