Machine Learning Researcher

Responsibilities

• Develop, implement, train, and iteratively improve state-of-the-art models for biomolecule design
• Analyze, visualize, and communicate results to support team efforts in improving models and data
• Create, deploy, and refine tools for efficient, reliable machine learning experimentation and production
• Work with biologists to collect data for the training and evaluation of generative models of biomolecules
• Provide mentorship and technical direction to team members as appropriate

Requirements

• 3+ years of hands-on experience developing ML models
• Demonstrated track record of implementing, training, and improving advanced machine learning models
• Highly capable programmer fluent in Python ecosystem and PyTorch or similar deep learning framework
• Availability to work with team members across US and Europe
• Readiness to travel several times a year for company retreats and business events
• Ability to work primarily from office locations in Berlin, Palo Alto, or Zurich

Preferred Qualifications

• PhD in AI/ML, computer science, computational biology, physics, or a related field
• Practical experience with modern generative models
• Strong software engineering skills for data processing and compute cluster orchestration
• Experience with large-scale model training, foundation models, and model parallelism
• Experience with bio sequence data, genomic/protein data, and functional assays
• Knowledge of biochemistry, molecular/cell biology, and drug development

Benefits

• Competitive compensation package including bonus and equity
• 30 days paid vacation per year
• Comprehensive health insurance
• 401K with company match (US) or Direktversicherung (Germany)
• Quarterly company-wide retreats
• Monthly wellness benefit
• Budget for office visits and Learning & Development

About the Company

Inceptive is creating tools to develop increasingly powerful biological software for the rational design of novel, broadly accessible medicines and biotechnologies. Our team combines expertise in molecular biology, machine learning, and software engineering to pioneer a new discipline rooted in biology and deep learning.