Description

SystImmune is a leading and well-funded clinical-stage biopharmaceutical company located in Redmond, WA and Princeton, NJ. It specializes in developing innovative cancer treatments using its established drug development platforms, focusing on bi-specific, multi-specific antibodies, and antibody-drug conjugates (ADCs). SystImmune has multiple assets in various stages of clinical trials for solid tumor and hematologic indications. Alongside ongoing clinical trials, SystImmune has a robust preclinical pipeline of potential cancer therapeutics in the discovery or IND-enabling stages, representing cutting-edge biologics development. We offer an opportunity for you to learn and grow while making significant contributions to the company’s success. With a growing pipeline and multiple clinical programs in solid tumors and hematologic malignancies, we are expanding our AI and computational discovery team to identify novel drug targets and design next-generation therapeutics. We are seeking a Machine Learning Frontier Scientist/Sr. Scientist with a proven track record applying AI to drug development, specifically in areas like target discovery, antibody or ADC engineering, and cancer immunotherapy. This is not a data management role. The ideal candidate will bring domain-specific expertise in oncology, immunology, or protein therapeutics and be comfortable operating at the frontier of ML applications in therapeutic design. Responsibilities<ul><li>Drug Target Discovery: Develop and apply ML/AI methods to identify and prioritize novel drug targets, including T cell engagers, ADCs, and multispecific antibodies.</li><li>Therapeutic Design: Engineer and optimize therapeutic strategies using ML models, including payload strategies and checkpoint combinations for cancer indications.</li><li>Model Development: Build scalable and interpretable machine learning models (e.g., DL, VAEs, GNNs) using public and internal multi-omics, structural, and clinical datasets.</li><li>Data Mining for Oncology: Analyze complex datasets (RNA-seq, proteomics, perturbation, clinical trial data) to generate actionable insights into cancer biology and treatment response.</li><li>Cross-functional Collaboration: Work closely with protein engineers, immunologists, and translational scientists to integrate AI-driven hypotheses into the drug pipeline.</li><li>Scientific Feedback Loop: Interpret outputs from ML models and guide experimental validation, providing insight into feasibility, mechanistic pathways, and therapeutic relevanc</li></ul>Qualifications<ul><li>PhD or Master’s in Computer Science, Machine Learning, Computational Biology, Bioinformatics, Biostatistics, or a related field.</li><li>5+ years of industry experience in drug discovery or therapeutic development required.</li><li>Strong experience with drug development platforms, ideally including target selection/validation and biologic modality development (ADC, TCE, antibodies).</li><li>Demonstrated application of ML/AI to therapeutic R&D (e.g., gene expression modeling, target nomination, protein interaction prediction).</li><li>Familiarity with oncology-focused discovery, especially involving immune checkpoints, payload strategies, or tumor-specific targets.</li><li>Hands-on proficiency with Python, R, PyTorch or TensorFlow, and related bioinformatics/ML tools.</li><li>Exposure to protein structure modeling or antibody engineering is highly desirable.</li><li>Experience with multi-modal data integration, including single-cell, bulk RNA-seq, proteomics, or clinical data.</li></ul><h2 style="margin-top:13px;">Preferred Experience</h2><ul><li>Prior work on T cell engagers, ADC programs, or bispecific antibodies.</li><li>Understanding of protein-ligand interactions, payload selection, or immune checkpoint design.</li><li>Knowledge of tools such as AlphaFold, Rosetta, DiffDock, or protein language models.</li><li>Experience working with drug development platforms across cancer and other disease areas.</li></ul><h2 style="margin-top:13px;">This role is not a fit for:</h2><ul><li>Generalist data scientists or clinical data managers without direct therapeutic development experience.</li><li>Candidates lacking domain exposure to biologics, oncology, or drug platform work.</li></ul><h2 style="margin-top:13px;">What We Offer</h2><ul><li>The opportunity to directly impact first-in-class cancer immunotherapies.</li><li>A collaborative and fast-moving environment bridging biology, engineering, and AI.</li><li>Access to internal pipelines, multi-omics data, and wet-lab teams for experimental feedback.</li><li>Competitive salary, stock options, and onsite culture in Redmond, WA.</li></ul> Compensation and Benefits: The expected base salary range for this position is $100,000 - $180,000 annually. Actual compensation will be based on a variety of factors, including but not limited to a candidate’s qualifications, experience, and skills. While most offers typically fall within the low to mid-point of the range, we may extend an offer toward the higher end for exceptional candidates whose background and expertise exceeds the requirements of the role.   SystImmune is a leading and well-funded biotech company with a bright future. We offer an opportunity for you to learn and grow while making significant contributions to the company’s success. SystImmune offers a comprehensive benefits package including: 100% paid employee premiums for medical/dental/vision, also STD, LTD, a 401(k) plan with a 50% company match of up to 3% and a vesting schedule of only 5 years, 15 PTO days per year, sick leave, plus 11 paid holidays and MORE.   We offer an opportunity for you to learn and grow while making significant contributions to the company’s success.   SystImmune is an Equal Opportunity Employer. We welcome diverse talent and encourage all qualified applicants to apply.

Machine Learning Scientist/Sr. Scientist - Drug Target Discovery

Description

SystImmune