Role Description Adaptive Biotechnologies is seeking a Senior Machine Learning Scientist to contribute to the development of deep learning models for TCR–pMHC specificity prediction. In this role, you will: - Design, implement, train, and evaluate machine learning models that predict interactions between T cell receptors and peptide–MHC complexes. - Integrate sequence and structural information in model development. - Work as part of a collaborative modeling team to implement new modeling ideas and improve predictive accuracy. - Leverage large-scale proprietary immune receptor datasets and shared GPU infrastructure for rapid experimentation and model development. - Collaborate closely with computational scientists, immunologists, and machine learning engineers. - Contribute to diagnostic and therapeutic initiatives both within Adaptive and through external partnerships. Qualifications - PhD in a quantitative discipline (e.g. Machine Learning, Computational Biology, Computer Science) + 5 years progressive experience applying machine learning to real-world scientific or biological problems OR 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. - 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. Requirements - Experience in one or more of the following areas desired: - Demonstrated track record of implementing novel machine learning solutions to biological problems, as demonstrated by publications, conference papers, patents, or delivered products. - Protein structure prediction. - Protein design and generative modeling. - Protein language models. - Large-scale biological datasets. - Immunology and immune receptor specificity (antibody or TCR). Benefits - Salary Range: $144,600 - $217,000 - Equity grant - Bonus eligible

Role Description Adaptive Biotechnologies is seeking a Principal Machine Learning Scientist to lead the development of deep learning models for TCR–pMHC specificity prediction. In this role, you will leverage a large and growing proprietary dataset to design, train, and evaluate models that predict interactions between T cell receptors and peptide–MHC complexes. Your work will focus on developing new approaches that integrate sequence and structural information and rigorously testing their performance in practical settings. You will work closely with computational scientists, immunologists, and machine learning engineers across the organization. The team brings together expertise in immune biology, experimental assay development, and large-scale machine learning, with access to proprietary immune receptor datasets, shared GPU infrastructure, and engineering support for model development and training. This role sits at the intersection of modeling and experimental data generation. As model results highlight gaps in available data or suggest new experimental directions, newly generated datasets can provide additional signal for improving and validating the models. Models developed in this role contribute directly to diagnostic and therapeutic initiatives both within Adaptive and through external partnerships. This position offers the opportunity to advance predictive modeling of immune receptor specificity while seeing those advances translated into meaningful clinical and commercial applications. Key Responsibilities and Essential Functions - 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. - Define Modeling and Data Strategy. - 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. - Drive Impact 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. Qualifications - 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. Preferred - Experience in one or more of the following areas desired: - Protein structure prediction. - Protein design and generative modeling. - Protein language models and large-scale foundation models. - Working with large-scale biological datasets. - Immunology and immune receptor specificity (antibody or TCR). Compensation - Salary Range: $183,400 - $275,000. - Other compensation elements include: - equity grant. - bonus eligible.

Title: AI/Machine Learning Specialist Clearance: Active TS Required, Q Clearance preferred Education: Bachelor’s degree preferred Years Experience: all levels available Location: fully remote Compensation: DOE ($90-$140/yr.) Overview: An AI/Machine Learning Specialist designs, develops, and implements AI solutions, leveraging techniques like machine learning and deep learning to solve complex business problems. They work closely with data scientists and engineers to create algorithms that drive data analysis and influence strategic decisions. Responsibilities: - Project Planning and Execution: This role involves strategizing and implementing ML projects. It requires a strong understanding of business objectives to develop project plans, coordinate resources, and oversee the project’s execution to deliver high-quality results on time. - Problem-Solving and Decision-Making: The ML Specialist is expected to leverage their technical expertise to solve complex problems. They must be capable of making critical decisions related to algorithm choice, data usage, and model implementation, which directly impact the project’s outcome. - Collaboration with Cross-Functional Teams: As part of their role, ML Specialists work closely with other departments such as data engineering, software development, and business intelligence. This collaboration ensures that ML projects align with broader company objectives and technological capabilities. - Leadership and Mentorship: In some cases, the ML Specialist may be required to lead a team of junior data scientists or analysts. This responsibility includes mentoring team members, overseeing their work, and contributing to their professional development. - Process Improvement and Innovation: A fundamental part of this role is to continuously seek ways to improve existing ML processes and algorithms. The ML Specialist is also expected to stay updated on industry trends and apply innovative techniques to maintain our competitive edge. - Technical or Customer-Facing Responsibilities: Lastly, an ML Specialist may be tasked with technical report writing, presenting findings to non-technical stakeholders, or even interacting with clients to understand their needs and deliver tailored ML solutions. Note This job description in no way states or implies that these are the only duties to be performed by the employee(s) of this position. Employees will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments. All duties and responsibilities are essential functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities. Who we are...  August Schell offers 30 years of experience in providing our customers innovative solutions and engineering services to their most challenging needs. We thrive on navigating complex IT difficulties and are driven to find the best solutions for our customers. Our team delivers expert knowledge in cyber security, big data, endpoint security and cloud solutions. Our ability to serve our customers with continued excellence is a direct reflection of our dedicated and exceptional people. At August Schell, we are not only a team, we are a family. Equal Employment Opportunity August Schell Enterprises Inc. is an Equal Employment Opportunity Employer. We are committed to providing a workplace that is free from discrimination and harassment based on race, color, religion, sex (including pregnancy, sexual orientation or gender identity), national origin, age, marital status, disability, protected veteran status or any other characteristic protected by applicable law. Accommodations If you are an individual with a disability and would like to request a reasonable accommodation during the application or hiring process, please contact Human Resources at hr@augustschell.com Apply Now

• Improve the performance of our machine learning models • Continuously oversee the performance of models in production and develop monitoring tools to gain deeper insights into areas for model performance enhancement • Collaborate with a team of researchers and engineers to design, implement and maintain innovative solutions to complex problems. • Reduce the training and inference time of our ML pipeline • Drive projects and lead new initiatives in MLOps