• 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 Dev Ops engineers for efficient deployment to production

• 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, Spa Cy, Hugging Face Transformers)
• Experience in at least one framework for Big Data (e.g., Ray, Spark) and one framework for Deep Learning (e.g., Py Torch, 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

• 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 No SQL databases, especially Mongo DB
• Familiarity with model registry solutions such as MLflow
• Familiarity with distributed computing platforms such as Ray and Spark

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

Work Where It’s Best for You

Work Anywhere means you can work in an office or at home on any given day. It’s about getting the work done in the way and place that works best for each person. This applies across all locations and departments.
Work Anywhere does not mean work at any time. We have predictable core hours where employees are generally available for meetings and collaboration. Employees are focused and available during core hours.
We invest in our offices to make them places where our employees like to go. If you work in the office three or more days a week, you will have a dedicated office workspace. Our offices function as hubs to draw people in, create social bonds, and where random connections and mixing of ideas happen. We’re investing more in offices, culture, and offsite meetings, not less.
Product teams are organized in regional product hubs for optimal collaboration and live within a time zone of their hub. Our current product hubs are located in Pleasanton, Columbus, Boston, Kansas City, New York City, Raleigh, and Toronto. We create opportunities for teams to get together in person regularly.
Customer-facing roles, such as Sales and Professional Services, live near and/or travel to their customers.
When an employee moves within a country it does not cause a change in salary. Where you live impacts you and your family. Not knowing if your compensation will change if you move can cause stress and uncertainty for everyone. We wanted to eliminate that.
Work at Veeva. Work where it’s best for you.