Machine Learning Scientist
Iambic Therapeutics
•
San Diego, CA
0
0
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Not Applicable
Posted April 3, 2026
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Responsibilities
Commitments
Responsibilities
- Design, implement, and train discrete and continuous diffusion models for predicting biomolecular structure tokens
- Develop and iterate on structure tokenizers, including vector-quantized representations of 3D molecular and protein structure
- Build and maintain data processing pipelines for large-scale biomolecular structure datasets
- Train models on multi-GPU clusters, managing large-scale training runs
- Develop rigorous benchmarking and evaluation workflows; validate against external benchmarks while prioritizing internal discovery-relevant metrics
- Collaborate with ML scientists, computational chemists, and drug discovery teams to integrate models into discovery workflows
- Communicate results to internal teams, external partners, and at scientific conferences
- Mentor interns and junior team members through code reviews, technical guidance, and best practices (Senior level)
Commitments
RS II and Senior candidates are expected to bring industry experience applying ML methods to drug discovery or related scientific domains
Senior candidates are expected to have a track record of independently driving research direction and mentoring others
Location
Remote (US or UK).
On-site available in Bristol, UK, and Boston, US.
We are in a brand-new state-of-the art facility in beautiful San Diego with an onsite gym, dining, and easy access to great places to live and play.
Not Met Priorities
What still needs stronger evidence
Requirements
- PhD in machine learning, computer science, computational chemistry, physics, or a related computational STEM field, or equivalent industry experience demonstrating comparable depth
- Strong Python and PyTorch skills, including end-to-end implementation and training of deep learning models
- Demonstrated experience in one or more of the following:
- 3D atomistic or molecular modeling
- Vector quantization and learned discrete representations
- Diffusion, flow-matching, or related generative modeling in continuous vector spaces
- Strong engineering practices: reproducible experimentation, clean code, testing, and performance-aware debugging
- Comfort with modern ML infrastructure (e.g., Docker, CUDA, Kubernetes, experiment tracking tools such as Weights & Biases)
- RS II and Senior candidates are expected to bring industry experience applying ML methods to drug discovery or related scientific domains
Preferred Skills
- Comfort with modern ML infrastructure (e.g., Docker, CUDA, Kubernetes, experiment tracking tools such as Weights & Biases)
- Experience with discrete diffusion, masked generative or transfusion models
- Protein–ligand modeling, structure prediction, or structure-based drug discovery
- Geometric deep learning and/or equivariant architectures
- Multi-GPU / distributed training at scale
- Docking, molecular dynamics, or other biomolecular simulation methods
- RS II and Senior candidates are expected to bring industry experience applying ML methods to drug discovery or related scientific domains
Education
- (Not required) – PhD in machine learning, computer science, computational chemistry, physics, or a related computational STEM field, or equivalent industry experience demonstrating comparable depth
Job Summary
We are seeking a Machine Learning Scientist to join Iambic Therapeutics and work on transformer-based diffusion methods for the prediction of biomolecular structure. In this role, you will develop generative models that operate over tokenized structural representations, contributing to the next generation of our core ML technologies including NeuralPLexer and Enchant.
This work sits at the intersection of generative modeling, structural biology, and representation learning. You will design and train structure tokenizers, build diffusion models over learned token spaces, curate and process large-scale biomolecular datasets, and benchmark model performance against state-of-the-art methods, all in service of accelerating drug discovery.
We are hiring across multiple levels (RS I, RS II, and Senior) and welcome candidates ranging from recent PhD graduates to experienced researchers with a strong publication or deployment record.
Key Responsibilities
Design, implement, and train discrete and continuous diffusion models for predicting biomolecular structure tokens
Develop and iterate on structure tokenizers, including vector-quantized representations of 3D molecular and protein structure
Build and maintain data processing pipelines for large-scale biomolecular structure datasets
Train models on multi-GPU clusters, managing large-scale training runs
Develop rigorous benchmarking and evaluation workflows; validate against external benchmarks while prioritizing internal discovery-relevant metrics
Collaborate with ML scientists, computational chemists, and drug discovery teams to integrate models into discovery workflows
Communicate results to internal teams, external partners, and at scientific conferences
Mentor interns and junior team members through code reviews, technical guidance, and best practices (Senior level)
Qualifications
Required
PhD in machine learning, computer science, computational chemistry, physics, or a related computational STEM field, or equivalent industry experience demonstrating comparable depth
Strong Python and PyTorch skills, including end-to-end implementation and training of deep learning models
Demonstrated experience in one or more of the following:
3D atomistic or molecular modeling
Vector quantization and learned discrete representations
Diffusion, flow-matching, or related generative modeling in continuous vector spaces
Strong engineering practices: reproducible experimentation, clean code, testing, and performance-aware debugging
Comfort with modern ML infrastructure (e.g., Docker, CUDA, Kubernetes, experiment tracking tools such as Weights & Biases)
Desired
Experience with discrete diffusion, masked generative or transfusion models
Protein–ligand modeling, structure prediction, or structure-based drug discovery
Geometric deep learning and/or equivariant architectures
Multi-GPU / distributed training at scale
Docking, molecular dynamics, or other biomolecular simulation methods
Depending on Level
RS II and Senior candidates are expected to bring industry experience applying ML methods to drug discovery or related scientific domains
Senior candidates are expected to have a track record of independently driving research direction and mentoring others
Location
Remote (US or UK). On-site available in Bristol, UK, and Boston, US.
About Iambic Therapeutics
Iambic is a clinical-stage life-science and technology company developing novel medicines using its AI-driven discovery and development platform. Based in San Diego and founded in 2020, Iambic has assembled a world-class team that unites pioneering AI experts and experienced drug hunters. The Iambic platform has demonstrated delivery of new drug candidates to human clinical trials with unprecedented speed and across multiple target classes and mechanisms of action. Iambic is advancing a pipeline of potential best-in-class and first-in-class clinical assets, both internally and in partnership, to address urgent unmet patient need. Learn more about the Iambic team, platform, pipeline, and partnerships at iambic.ai.
MISSION & CORE VALUES
Our mission is to deliver better medicines through innovations in AI-based discovery technologies. The culture and work at Iambic Therapeutics are profoundly strengthened by the diversity of our people and our differences in background, culture, national origin, religion, sexual orientation, and life experiences. We are committed to building an inclusive environment where a diverse group of talented humans work together to discover therapeutics and create technologies.
Pay And Benefits
We offer industry leading competitive pay, company paid healthcare, flexible spending accounts, voluntary life insurance, 401K matching, and uncapped vacation to our team. We are in a brand-new state-of-the art facility in beautiful San Diego with an onsite gym, dining, and easy access to great places to live and play.
Compensation Range: $148.8K - $235K
We are seeking a Machine Learning Scientist to join Iambic Therapeutics and work on transformer-based diffusion methods for the prediction of biomolecular structure. In this role, you will develop generative models that operate over tokenized structural representations, contributing to the next generation of our core ML technologies including NeuralPLexer and Enchant.
This work sits at the intersection of generative modeling, structural biology, and representation learning. You will design and train structure tokenizers, build diffusion models over learned token spaces, curate and process large-scale biomolecular datasets, and benchmark model performance against state-of-the-art methods, all in service of accelerating drug discovery.
We are hiring across multiple levels (RS I, RS II, and Senior) and welcome candidates ranging from recent PhD graduates to experienced researchers with a strong publication or deployment record.
Key Responsibilities
Design, implement, and train discrete and continuous diffusion models for predicting biomolecular structure tokens
Develop and iterate on structure tokenizers, including vector-quantized representations of 3D molecular and protein structure
Build and maintain data processing pipelines for large-scale biomolecular structure datasets
Train models on multi-GPU clusters, managing large-scale training runs
Develop rigorous benchmarking and evaluation workflows; validate against external benchmarks while prioritizing internal discovery-relevant metrics
Collaborate with ML scientists, computational chemists, and drug discovery teams to integrate models into discovery workflows
Communicate results to internal teams, external partners, and at scientific conferences
Mentor interns and junior team members through code reviews, technical guidance, and best practices (Senior level)
Qualifications
Required
PhD in machine learning, computer science, computational chemistry, physics, or a related computational STEM field, or equivalent industry experience demonstrating comparable depth
Strong Python and PyTorch skills, including end-to-end implementation and training of deep learning models
Demonstrated experience in one or more of the following:
3D atomistic or molecular modeling
Vector quantization and learned discrete representations
Diffusion, flow-matching, or related generative modeling in continuous vector spaces
Strong engineering practices: reproducible experimentation, clean code, testing, and performance-aware debugging
Comfort with modern ML infrastructure (e.g., Docker, CUDA, Kubernetes, experiment tracking tools such as Weights & Biases)
Desired
Experience with discrete diffusion, masked generative or transfusion models
Protein–ligand modeling, structure prediction, or structure-based drug discovery
Geometric deep learning and/or equivariant architectures
Multi-GPU / distributed training at scale
Docking, molecular dynamics, or other biomolecular simulation methods
Depending on Level
RS II and Senior candidates are expected to bring industry experience applying ML methods to drug discovery or related scientific domains
Senior candidates are expected to have a track record of independently driving research direction and mentoring others
Location
Remote (US or UK). On-site available in Bristol, UK, and Boston, US.
About Iambic Therapeutics
Iambic is a clinical-stage life-science and technology company developing novel medicines using its AI-driven discovery and development platform. Based in San Diego and founded in 2020, Iambic has assembled a world-class team that unites pioneering AI experts and experienced drug hunters. The Iambic platform has demonstrated delivery of new drug candidates to human clinical trials with unprecedented speed and across multiple target classes and mechanisms of action. Iambic is advancing a pipeline of potential best-in-class and first-in-class clinical assets, both internally and in partnership, to address urgent unmet patient need. Learn more about the Iambic team, platform, pipeline, and partnerships at iambic.ai.
MISSION & CORE VALUES
Our mission is to deliver better medicines through innovations in AI-based discovery technologies. The culture and work at Iambic Therapeutics are profoundly strengthened by the diversity of our people and our differences in background, culture, national origin, religion, sexual orientation, and life experiences. We are committed to building an inclusive environment where a diverse group of talented humans work together to discover therapeutics and create technologies.
Pay And Benefits
We offer industry leading competitive pay, company paid healthcare, flexible spending accounts, voluntary life insurance, 401K matching, and uncapped vacation to our team. We are in a brand-new state-of-the art facility in beautiful San Diego with an onsite gym, dining, and easy access to great places to live and play.
Compensation Range: $148.8K - $235K