Superluminal Medicines, Inc.
Pick a job to read the details
Tap any role on the left — its description and apply link will open here.
Machine Learning Engineer
Share this job
About Superluminal Medicines:
Superluminal Medicines is a generative biology and chemistry company revolutionizing the speed and accuracy of how small molecule medicines are created. The Company’s platform aims to create candidate-ready compounds with unprecedented speed using a combination of deep biology, computational and medicinal chemistry, machine learning, and proprietary big data infrastructure. We are expanding the team of talented scientists who seek to build the future of small molecule drug discovery with creativity and innovation.
About the Role:
We are seeking a high-impact Machine Learning Developer/Engineer to join our integrated discovery team. In this role, you will be the algorithmic engine of our programs, developing and deploying state-of-the-art ML models to generate the quantitative predictions necessary to drive drug discovery. Beyond technical mastery, you will serve as a core scientific partner to medicinal chemists, computational chemists, and biologists, building models that move programs efficiently toward Go/No-Go decision points and candidate nomination.
Key Responsibilities:
- Implement algorithms for hit identification through virtual screening and other high throughput computational methods as part of a cross-functional team
- Adapt and implement cutting-edge ML architectures for co-folding to augment our extensive internal structural biology expertise and capabilities
- Design and deploy active learning frameworks that utilize experimental assay results to iteratively improve model performance and reduce the number of "Design-Make-Test-Analyze" cycles leveraging state-of-the-art de novo design, ADMET predictions, and affinity predictions
Required Qualifications:
- Ph.D. preferred in Computer Science, Machine Learning, Engineering or a related field, or BS/MS + seasoned experience
- Proven experience with protein-ligand co-folding algorithms (e.g., Boltz, AlphaFold, OpenFold, etc) and the ability to integrate these structural insights into broader ML discovery pipelines.
- Advanced proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow) is required. You must be capable of building and maintaining production-quality code and data pipelines.
- Exceptional ability to communicate the "why" behind a design to a diverse scientific audience.
Preferred Qualifications:
- Expert-level knowledge of deep learning frameworks, specifically for affinity prediction, ADMET modeling, and the application of LLMs in a biological or chemical context
- Expertise fine-tuning existing models with internally generated structural biology and biology data
- Experience deploying ML/AI algorithms for use by a cross-functional scientific audience
- 1-4+ years of experience in a biotech or pharma setting
Skills & Competencies:
- A demonstrated track record of innovation in the ML/AI space, including developing and validating new architectures or novel applications of existing models to solve complex drug discovery problems including tools for hit identification (virtual screening, HTS)
- Expert level use of protein-ligand co-folding algorithms to small molecule drug discovery ML/AI tools (AlphaFold, Boltz, OpenFold)
- Experience writing production-level code for ML tasks:
- Knowledge of key scientific packages (RDKit, scikit-learn, numpy, pandas, pytorch, deepchem, polars, PyG/DGL):
- Write robust, testable, and version-controlled code that adheres to CI/CD and data governance best practices.
- Value clarity, documentation, and structured thinking, especially when working with complex data
- Knowledge of containerization technologies (Docker, Kubernetes) and cloud deployment at scale
Benefits:
Superluminal offers a comprehensive benefits package that fully covers employees’ annual deductibles and monthly premiums for medical, dental, and vision insurance. The package also includes a 401(k) match program, a Massachusetts transportation subsidy, equity, unlimited paid time off, and both disability and life insurance.
Equal Opportunity Statement:
Superluminal Medicines is an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status.
Ready to apply?
Apply to Superluminal Medicines, Inc.
Principal Scientist/Associate Director, Machine Learning
Share this job
About Superluminal Medicines:
Superluminal Medicines is a generative biology and chemistry company revolutionizing the speed and accuracy of how small molecule medicines are created. The Company’s platform aims to create candidate-ready compounds with unprecedented speed using a combination of deep biology, computational and medicinal chemistry, machine learning, and proprietary big data infrastructure. We are expanding the team of talented scientists who seek to build the future of small molecule drug discovery with creativity and innovation.
About the Role:
We are seeking a high-impact Machine Learning Scientist to join our integrated discovery team. In this role, leading from the bench, you will enable the development, validation and deployment of state-of-the-art ML models to generate the quantitative predictions necessary to drive drug discovery. Beyond technical mastery, you will serve as a core strategic partner to medicinal chemists, computational chemists, and biologists, building models that move programs efficiently toward Go/No-Go decision points and candidate nomination. This role may be responsible for the management and development of individual team members.
Key Responsibilities:
- Lead the application of Large Language Models (LLMs), co-folding algorithms, and generative chemistry techniques to design novel chemical matter aimed at hitting key program milestones, such as establishing selectivity windows and optimizing drug-like properties
- ML lead on project teams, collaborating intimately with medicinal chemists to refine SAR and with structural biologists to integrate co-folding and structure-based insights into ML workflows
- Data-Driven Decision Making: Synthesize complex ML outputs into clear, actionable design hypotheses that cross-functional scientific stakeholders can use to make high-stakes program decisions
- May be responsible for management and development of internal team members
Required Qualifications:
- Ph.D. in Computational Chemistry, Computer Science, Machine Learning, or a related field
- Demonstrated expertise in statistics, probability theory, data modeling, machine learning algorithms, and the languages used to implement analytics solutions
- 4-7+ years of experience in a biotech or pharma setting performing ML support for small molecule drug discovery with clear evidence of impact on drug discovery programs
- Demonstrated success in a cross-functional environment, including biologists, structural biologists, medicinal and computational chemists, with specific examples of computational designs/algorithms/models that directly led to the achievement of program milestones
- Expert proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow) is required. You must be able to build and maintain production-quality code and data pipelines
Preferred Qualifications:
- Proven experience with protein-ligand co-folding models (e.g.,Boltz, OpenFold, AlphaFold, etc) and the ability to integrate these structural insights into broader ML discovery pipelines
- Expertise fine-tuning existing models with internally generated structural biology and biology data
- Expert-level knowledge of deep learning frameworks, specifically for affinity prediction, ADMET modeling, and the application of LLMs in a biological or chemical context
Skills & Competencies:
- A demonstrated track record of innovation in the ML/AI space, including developing and validating new architectures or novel applications of existing models to solve complex drug discovery problems
- Demonstrated expertise using small molecule drug discovery ML/AI tools (AlphaFold, Boltz, OpenFold, ChemProp, DeepChem, Reinvent, etc)
- Expert level coding for ML tasks including knowledge of key packages (RDKit, scikit-learn, numpy, pandas, pytorch, DeepChem, polars, PyG/DGL).
- Strong interpersonal and communications skills in the "why" behind a design to a diverse scientific audience
- Experience mentoring and developing teams
Benefits:
Superluminal offers a comprehensive benefits package that fully covers employees’ annual deductibles and monthly premiums for medical, dental, and vision insurance. The package also includes a 401(k) match program, a Massachusetts transportation subsidy, equity, unlimited paid time off, and both disability and life insurance.
Equal Opportunity Statement:
Superluminal Medicines is an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status.
Ready to apply?
Apply to Superluminal Medicines, Inc.