Do you want to join a team where the mission is meaningful, the challenges are complex, and you can directly see the results of your hard work? Lundbeck is a global biopharmaceutical company focusing exclusively on brain health. With more than 70 years of experience in neuroscience, we are committed to improving the lives of people with neurological and psychiatric diseases. Lundbeck employees are inspired and driven by our purpose to advance brain health and transform lives. Join us on our journey of growth!

POSITION SUMMARY:

Lundbeck US is seeking a dynamic, motivated, and highly skilled individual for the position of AI Engineer. In this role, you will work on cutting-edge projects that involve creating AI applications that generate human-like content, automate tasks, and provide innovative solutions to complex problems. The ideal candidate will have hands-on experience with LLMs, such as GPT, BERT, or similar models, and will be responsible for integrating and optimizing these models to deliver powerful, real-world AI-driven solutions.

REQUIRED EDUCATION, EXPERIENCE, AND SKILLS:

• Accredited Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 3+ years of relevant experience in AI/ML model development, deployment, and optimization.
• Proven experience developing Generative AI applications, including content generation, conversational AI, and natural language understanding tasks.
• Strong proficiency in programming languages such as Python, Java or C++.
• Familiarity with deployment frameworks like Flask, FastAPI, or Streamlit to create APIs or web apps that serve LLM-powered applications.
• Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying AI models and applications at scale.
• Familiarity with AI deployment techniques, including Docker and Kubernetes for scalable production environments.
• Strong problem-solving ability to design, develop, and optimize AI applications to meet specific business needs.
• Ability to collaborate with cross-functional teams to drive the successful deployment and integration of AI solutions.

PREFERRED EDUCATION, EXPERIENCE, AND SKILLS:

• Accredited Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Familiarity with LangChain for building conversational AI applications and workflows utilizing LLMs.
• Experience in Retrieval-Augmented Generation (RAG) systems that combine LLMs with external knowledge bases to enhance output relevance.
• Experience deploying LLMs at scale, ensuring they are optimized for low-latency responses, high availability, and fault tolerance in production.
• In-depth experience working with pharmaceutical datasets (first-party patient data, third-party claims, EHR, demand data).
• Familiarity with regulatory standards in the pharmaceutical industry (e.g., GxP, ALCOA+).

• Develop and implement applications using GenAI for tasks such as text generation, summarization, question-answering, and more.
• Design and build end-to-end AI applications, including data processing, model integration, and deployment, to deliver seamless AI-driven solutions.
• Implement feedback loops to continuously improve and optimize the ML/AI models, ensuring real-time effectiveness and adaptability in production environments.
• Fine-tune pre-trained LLMs on domain-specific data to improve model accuracy, performance, and relevance in generating context-specific content.
• Integrate AI-powered features into existing systems and products, enhancing user experiences with context-aware and highly engaging AI capabilities.
• Design user-facing solutions that leverage the generative power of AI to provide dynamic content creation, natural conversations, and automated content generation for various business needs.
• Collaborate with business stakeholders to understand requirements and develop solutions that align with company goals.
• Manage the entire data pipeline: from preprocessing and cleaning data to transforming and embedding data for LLM training or inference.
• Ensure effective data management for training, fine-tuning, and inference processes by using appropriate databases and cloud platform