Principal Machine Learning Scientist

🔥 12 hours ago

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Adaptive Biotechnologies Corp.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2009

🧬 Biotechnology

⚕️ Healthcare Insurance

💊 Pharmaceuticals

💰 $125M Post-IPO Debt on 2022-09

Biotechnology • Healthcare Insurance • Pharmaceuticals

Adaptive Biotechnologies Corp. is a leader in immune-driven medicine, aiming to revolutionize disease detection and treatment. By utilizing the adaptive immune system, the company develops diagnostic and therapeutic solutions powered by its innovative Immune Medicine platform. They offer clinical diagnostics, particularly in Minimal Residual Disease (MRD) testing, and engage in drug discovery and therapeutic development through adaptive immunosequencing technologies. Their biopharma services support the progression of clinical trials and the development of transformative medicines. Adaptive Biotechnologies leverages the complex biology of the immune system, decoding it to advance medical science and improve patient outcomes.

📋 Description

• Design, implement, and train novel deep learning architectures for TCR–pMHC specificity prediction. • Extend and adapt advances in protein language models, structure prediction, generative modeling, and representation learning to the immune receptor setting. • Leverage and influence scalable training infrastructure to support large-scale model development and experimentation. • Lead 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. • Evaluate emerging ML advances and determine when and how to incorporate them into Adaptive’s modeling roadmap. • Shape the long-term technical direction of machine learning in immune receptor prediction across the organization. • Partner with computational biology, immunology, translational, and engineering teams to ensure models are capable, scalable, reproducible, and aligned with therapeutic and diagnostic goals. • Clearly communicate complex modeling insights to scientific leadership, executives, and external partners. • Contribute to intellectual property development and high-impact publications.

🎯 Requirements

• PhD in a quantitative discipline (e.g. Machine Learning, Computational Biology, Computer Science, etc.) + 12 years progressive experience in machine learning, applied statistics or related field in a life sciences or biotech environment or similar combination of education and experience; an advanced degree preferred. • Masters + 15 years of progressive experience, or • Bachelors + 17 years of progressive experience • Progressive experience in the conception, development and deployment of deep learning methods including substantial hands-on model development • Demonstrated track record of innovating and implementing novel machine learning solutions to biological problems, as demonstrated by publications, conference papers, patents, or delivered products. • Deep expertise in python and modern ML tooling (PyTorch preferred) • Experience with version control and ML experiment tracking • Proven ability to independently define, scope, and execute complex technical research problems. • Excellent written and verbal communication skills, with ability to present highly technical material to diverse audiences. • Exceptional depth in deep learning architecture design and implementation. • Comfortable operating at the frontier of both ML and immunology. • Strategic thinker capable of influencing technical direction across teams. • Driven by impact: motivated to see models transition from research to clinical and commercial application.

🏖️ Benefits

• equity grant • bonus eligible