Research Scientist (Machine Learning) (AI)

Location: Lausanne, Switzerland; hybrid working with office attendance required 3 days per week

Company

hirify.global develops AI models and a drug design engine to accelerate scientific discovery and rational drug design.

What you will do

• Develop novel machine learning techniques, model architectures, and training algorithms for drug discovery.
• Create and prepare data required to train machine learning models.
• Analyse and tune experimental results to guide future research directions.
• Implement and scale training and inference engineering frameworks.
• Present research findings clearly to machine learning scientists and interdisciplinary scientific teams.
• Depending on experience, lead research projects, mentor researchers, and provide project or people management.

Requirements

• PhD or equivalent practical experience in a technical field.
• Proven experience applying deep learning, including architecture design, experimentation, analysis, and visualisation.
• Strong knowledge of linear algebra, calculus, and statistics.
• Experience with JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas.
• Passion for applying machine learning research to real-world problems.
• Depending on experience, project supervision, leadership, or management experience.

Nice to have

• PhD in machine learning or computer science, postdoctoral experience, publications, or contributions to machine learning codebases.
• Experience working across biology, chemistry, or physics, including biological or chemical data and software.
• Experience with real-world datasets, accelerators, large-scale deep learning, generative models, graph neural networks, or applied reinforcement learning.
• Experience with deep learning for drug discovery, computer vision, 3D graphics, or robotics.

Culture & Benefits

• Interdisciplinary collaboration between machine learning scientists, engineers, and domain experts.
• Culture guided by curiosity, creativity, care, initiative, integrity, determination, and collaboration.
• Hybrid working model designed to support knowledge sharing and in-person relationships.
• Commitment to an inclusive workplace and equal employment opportunities.