Generative AI Engineer - Molecular Design Optimization

Qualifications

• Ph.D. in Computer Science (with AI/ML specialization), Computational Biology/Chemistry (with significant ML method development), or a closely related field
• Deep theoretical understanding and extensive hands-on experience building and training state-of-the-art generative deep learning models
• Strong practical experience implementing and applying advanced optimization techniques, particularly Reinforcement Learning and/or Evolutionary Algorithms, ideally in a scientific discovery context
• Experience working with molecular representations (sequences, graphs) and relevant libraries (e.g., RDKit, DeepChem, PyG, BioPython)
• Proven ability to develop novel algorithms and implement complex ML systems
• Excellent programming skills and software engineering practices
• Strong analytical and problem-solving abilities
• Excellent communication and collaboration skills
• A creative and rigorous AI/ML researcher and engineer passionate about scientific discovery
• Possess a strong drive to build robust, cutting-edge AI systems
• Data-driven, pragmatic, and results-oriented
• Operate with high agency, proactively identifying challenges, defining solutions, and driving progress with no supervision in a fast-paced, ambiguous environment
• An excellent collaborator capable of working effectively at the interface of AI and physical sciences
• Adaptable and thrives in a dynamic startup environment

Benefits

• Pay: $150,000.00 - $240,000.00 per year
• 401(k)
• Dental insurance
• Health insurance
• Paid time off
• Vision insurance

Responsibilities

• Role Summary: As the AI Scientist / Generative Molecular Design Lead, you will be a critical member of our founding technical team, responsible for conceptualizing, building, and deploying the core AI engine that designs novel biomolecules
• You will leverage state-of-the-art generative models and optimization techniques to explore chemical space and create molecules meeting complex criteria
• You will work closely with simulation experts to integrate design generation with physics-based evaluation
• Lead the design, implementation, training, and validation of advanced Generative Models (e.g., Transformers, Diffusion Models, generative GNNs, VAEs) for the de novo design of biomolecules
• Develop and implement effective conditioning strategies to guide molecular generation based on target information and desired properties
• Design, implement, and tune sophisticated multi-objective optimization algorithms (e.g., Reinforcement Learning, Evolutionary Algorithms, Bayesian Optimization) to drive the design cycle towards candidates meeting complex requirements
• Build, maintain, and iterate on robust machine learning pipelines for training, inference, and optimization
• Stay abreast of the latest research in generative AI, geometric deep learning, RL, and their application to molecular design

Full Description

Company Description: Grafton Biosciences is a biotech startup focused on solving disease through groundbreaking innovations in early detection, diagnostics, and therapeutics. We are combining cutting-edge molecular and synthetic biology, machine learning, device engineering, and manufacturing to fundamentally extend healthy human lifespans. We’re looking for passionate team members who want to shape the future.

Role Summary: As the AI Scientist / Generative Molecular Design Lead, you will be a critical member of our founding technical team, responsible for conceptualizing, building, and deploying the core AI engine that designs novel biomolecules. You will leverage state-of-the-art generative models and optimization techniques to explore chemical space and create molecules meeting complex criteria. You will work closely with simulation experts to integrate design generation with physics-based evaluation.

Key Responsibilities:

• Lead the design, implementation, training, and validation of advanced Generative Models (e.g., Transformers, Diffusion Models, generative GNNs, VAEs) for the de novo design of biomolecules.

• Develop and implement effective conditioning strategies to guide molecular generation based on target information and desired properties.

• Design, implement, and tune sophisticated multi-objective optimization algorithms (e.g., Reinforcement Learning, Evolutionary Algorithms, Bayesian Optimization) to drive the design cycle towards candidates meeting complex requirements.

• Build, maintain, and iterate on robust machine learning pipelines for training, inference, and optimization.

• Stay abreast of the latest research in generative AI, geometric deep learning, RL, and their application to molecular design.

Required Qualifications:

• Ph.D. in Computer Science (with AI/ML specialization), Computational Biology/Chemistry (with significant ML method development), or a closely related field.

• Deep theoretical understanding and extensive hands-on experience building and training state-of-the-art generative deep learning models.

• Strong practical experience implementing and applying advanced optimization techniques, particularly Reinforcement Learning and/or Evolutionary Algorithms, ideally in a scientific discovery context.

• Expertise in modern deep learning frameworks (PyTorch strongly preferred; TensorFlow/JAX acceptable) and scientific Python libraries (NumPy, SciPy).

• Experience working with molecular representations (sequences, graphs) and relevant libraries (e.g., RDKit, DeepChem, PyG, BioPython).

• Proven ability to develop novel algorithms and implement complex ML systems.

• Excellent programming skills and software engineering practices.

• Strong analytical and problem-solving abilities.

• Excellent communication and collaboration skills.

Preferred Qualifications:

• Direct experience applying generative models or RL to biomolecule design.

• Experience with multi-objective optimization techniques.

• Familiarity with physics-informed machine learning concepts.

• Experience with MLOps practices and cloud computing platforms (AWS/GCP/Azure).

• Basic understanding of chemistry/biology/biophysics concepts.

Who You Are:

• A creative and rigorous AI/ML researcher and engineer passionate about scientific discovery.

• Possess a strong drive to build robust, cutting-edge AI systems.

• Data-driven, pragmatic, and results-oriented.

• Operate with high agency, proactively identifying challenges, defining solutions, and driving progress with no supervision in a fast-paced, ambiguous environment.

• An excellent collaborator capable of working effectively at the interface of AI and physical sciences.

• Adaptable and thrives in a dynamic startup environment.

Job Type: Full-time

Pay: $150,000.00 - $240,000.00 per year

Benefits:

• 401(k)

• Dental insurance

• Health insurance

• Paid time off

• Vision insurance

Application Question(s):

• Why are you a fit for this role?

• How soon can you begin?

Work Location: Remote