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Link is a pillar in the Veeva system landscape that envisions Connecting life sciences and key people to improve research and care. Our product offers real-time academics, social, and medical data to build comprehensive profiles. These profiles help our life-science industry partners find the right experts to accelerate the development and the adoption of new therapeutics. We accelerate clinical trials and equitable care. We are proud that our work helps patients receive their most urgent care sooner.

Your role will primarily involve developing LLM-based agents that are specialized in searching and extracting detailed information about Key Opinion Leaders (KOLs) in the healthcare sector. You will craft an end-to-end human-in-the-loop pipeline to sift through a large array of unstructured medical documents—ranging from academic articles to clinical guidelines and meeting notes from therapeutic committees. These agents will be equipped to perform semantic searches and provide precise answers to predefined queries concerning KOL-related data across various languages and disciplines. Utilizing cloud infrastructure, you will build models capable of information extraction and question answering. You will also collaborate with a dedicated team of software developers and DevOps engineers to refine these models and deploy them into production environments.

We want to develop new algorithms to redefine the industry expectations for quality vs. quantity compromise. We train ML models empowered by over 2000 curators to meet both the quality and the scale requirements. ML models complement and learn from continuous curation and scale our solutions to different regions, languages, and medical specialties.

You can work remotely from anywhere in the Netherlands, the UK, or Spain, but you must be a resident of one of these countries and be legally authorized to work there without requiring Veeva's support for a visa or relocation. If you do not meet this condition, but you think you are an exceptional candidate please clarify it in a separate note and we will consider it.

What You'll Do

• Adopt the latest technologies and trends in NLP to your platform
• Develop LLM-based agents capable of performing function calls and utilizing tools such as browsers for enhanced data interaction and retrieval
• Experience with Reinforcement Learning from Human Feedback (RLHF) methods such as Direct Preference Optimization (DPO) and Proximal Policy Optimization (PPO) for training LLMs based on human preferences
• Design, develop, and implement an end-to-end pipeline for extracting predefined categories of information from large-scale, unstructured data across multi-domain and multilingual settings
• Create a robust semantic search functionality that effectively answers user queries related to various aspects of the data
• Use and develop named entity recognition, entity-linking, slot-filling, few-shot learning, active learning, question/answering, dense passage retrieval, and other statistical techniques and models for information extraction and machine reading
• Deeply understand and analyze our data model per data source and geo-region and interpret model decisions
• Collaborate with data quality teams to define annotation task metrics, and perform qualitative and quantitative evaluation
• Utilize cloud infrastructure for model development, ensuring seamless collaboration with our team of software developers and DevOps engineers for efficient deployment to production

Requirements

• 4+ years of experience as a data scientist (or 2+ years with a Ph.D. degree)
• Master's or Ph.D. in Computer Science, Artificial Intelligence, Computational Linguistics, or a related field
• Strong theoretical knowledge of Natural Language Processing, Machine Learning, and Deep Learning techniques
• Proven experience working with large language models and transformer architectures, such as GPT, BERT, or similar
• Familiarity with large-scale data processing and analysis, preferably within the medical domain
• Proficiency in Python and relevant NLP libraries (e.g., NLTK, SpaCy, Hugging Face Transformers)
• Experience in at least one framework for BigData (e.g., Ray, Spark) and one framework for Deep Learning (e.g., PyTorch, JAX)
• Experience working with cloud infrastructure (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes) and experience with bashing script
• Strong collaboration and communication skills, with the ability to work effectively in a cross-functional team
• Used to start-up environments
• Social competence and a team player
• High energy and ambitious
• Agile mindset

Nice to Have

• Background in Medical NLP
• Experience with training, fine-tuning, and serving Large Language Models
• Experience in life/health science industry, notably pharma
• Having published in AI space in a peer-reviewed journal
• Production-grade development Skills
• Leadership skills and a solid network to help in hiring and growing the team
• Experience with NoSQL databases, especially MongoDB
• Familiarity with model registry solutions such as MLflow
• Familiarity with distributed computing platforms such as Ray and Spark

Perks & Benefits

• Work anywhere
• Personal development budget
• Veeva charitable giving program
• Fitness reimbursement
• Life insurance + pension fund