Senior Machine Learning Scientist

Adaptive Biotechnologies Corp.; United States; On-site; USD 145,000 - 217,000; Full time

Job summary

Adaptive Biotechnologies is seeking a Senior Machine Learning Scientist to contribute to TCR–pMHC specificity prediction. You will design, implement, train, and evaluate models that integrate sequence and structural information, leveraging large immune receptor datasets and shared GPUs.

You will work with computational biology, immunology, and ML engineering teams to ensure models are robust, reproducible, and ready for clinical and commercial applications, with opportunities to publish and

Qualifications

• PhD in a quantitative discipline with 5+ years ML experience in scientific problems.
• Progressive experience in development and deployment of deep learning methods.
• Strong hands-on Python and ML tooling (PyTorch preferred).
• Experience with protein structure prediction or analysis.
• Experience with large datasets and HPC environments.
• Ability to scope and execute complex technical research problems.
• Strong written and verbal communication and cross-functional collaboration.

Responsibilities

• Design, implement, train, and iterate on novel deep learning models for TCR–pMHC specificity prediction.
• Adapt protein structure prediction and interaction modeling to the immune receptor setting.
• Conduct rigorous benchmarking and evaluation strategies to ensure models are scientifically sound and practically superior.
• Translate biological principles of T cell recognition into principled modeling decisions.
• Influence large‑scale experimental data generation to maximize modeling leverage and long‑term performance gains.
• Provide technical recommendations to broader modeling discussions and roadmap planning.
• Work closely with computational biology, immunology, translational, and engineering teams to ensure models are robust, reproducible, and aligned with overall product goals.
• Communicate modeling insights, approaches, and results to cross‑functional scientific audiences.
• Contribute to publications, presentations, etc. through technical execution and analysis.
• All other duties as assigned.

Skills

Python

PyTorch

Deep learning

HPC

Education

PhD in a quantitative discipline

Job description

At Adaptive, we’re Powering the Age of Immune Medicine. Our goal is to harness the power of the adaptive immune system to transform the way diseases are diagnosed and treated.

Position Overview

Adaptive Biotechnologies is seeking a Senior Machine Learning Scientist to contribute to the development of models for TCR–pMHC specificity prediction. In this role, you will design, implement, train, and evaluate models that predict interactions between T cell receptors and peptide–MHC complexes, with a focus on integrating sequence and structural information. Working as part of a collaborative modeling team, you will implement new modeling ideas, rigorously test their performance, and iterate quickly to improve predictive accuracy. This work leverages large-scale proprietary immune receptor datasets and shared GPU infrastructure to support rapid experimentation and model development. You will work closely with computational scientists, immunologists, and machine learning engineers across the organization. The team combines expertise in immune biology, experimental assay development, and large-scale machine learning, enabling a tight feedback loop between model development and experimental data generation. Model outputs often highlight gaps in available data or suggest new experimental directions, while newly generated datasets provide additional signal for improving and validating predictive models. Models developed in this role contribute directly to diagnostic and therapeutic initiatives both within Adaptive and through external partnerships. This role is well suited for a hands‑on scientist who thrives in a collaborative environment and is motivated to translate cutting‑edge machine learning into meaningful biological and clinical impact.

Key Responsibilities And Essential Functions

• Design, implement, train, and iterate on novel deep learning models for TCR–pMHC specificity prediction.
• Adapt and extend advances in protein structure prediction and protein‑protein interaction modeling to the immune receptor setting.
• Conduct rigorous benchmarking and evaluation strategies to ensure models are scientifically sound and practically superior.
• Translate biological principles of T cell recognition into principled modeling decisions.
• Influence large‑scale experimental data generation to maximize modeling leverage and long‑term performance gains.
• Provide technical recommendations to broader modeling discussions and roadmap planning.
• Work closely with computational biology, immunology, translational, and engineering teams to ensure models are robust, reproducible, and aligned with overall product goals.
• Communicate modeling insights, approaches, and results to cross‑functional scientific audiences.
• Contribute to publications, presentations, etc. through technical execution and analysis.
• All other duties as assigned.

Position Requirements

• PhD in a quantitative discipline (e.g. Machine Learning, Computational Biology, Computer Science, etc.) + 5 years progressive experience applying machine learning to real‑world scientific or biological problems OR an equivalent combination of education and experience.
• Progressive experience in the development and deployment of deep learning methods.
• Strong hands‑on experience in Python and modern ML tooling (PyTorch preferred).
• Strong experience in deep learning architecture design and implementation.
• Strong experience with protein structure prediction or analysis.
• Experience working with large datasets and high‑performance computing environments.
• Ability to independently define, scope, and execute complex technical research problems.
• Strong written and verbal communication skills, with ability to present highly technical material to diverse audiences.
• Demonstrated ability to collaborate effectively in cross‑functional, multi‑disciplinary teams.
• Driven by impact: motivated to see models transition from research to clinical and commercial application.

Preferred

• Demonstrated track record of implementing novel machine learning solutions to biological problems, as demonstrated by publications, conference papers, patents, or delivered products.
• Protein‑protein interaction modeling.
• Molecular dynamics and/or free energy perturbation methods.
• Immunology and immune receptor specificity (antibody or TCR).

Compensation

Salary Range: $144,600 - $217,000

Other Compensation Elements Include

• Equity grant.
• Bonus eligible.

Equal Opportunity Employer

Adaptive Biotechnologies is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against based on disability. If you’d like to view a copy of the company’s affirmative action plan or policy statement, please email [e-mail]. If you have a disability and need reasonable accommodation to search for a job opening or submit an online application, please email [e-mail]. Only messages left for this purpose will be returned. Messages left for other purposes will not receive a response.