SystImmune
Senior/Principal Scientist – AI/ML Protein & Antibody Drug Discovery
SystImmune, Redmond, Washington, United States, 98052
Senior/Principal Scientist – AI/ML Protein & Antibody Drug Discovery
SystImmune is a leading and well‑funded clinical‑stage biopharmaceutical company located in Redmond, WA and Princeton, NJ, specializing in developing innovative cancer treatments using bi‑specific, multi‑specific antibodies and antibody‑drug conjugates (ADCs). We are seeking a highly skilled Senior or Principal Scientist with deep expertise in AI/ML and protein or antibody drug discovery to drive the design and implementation of advanced machine learning models and data infrastructure for our biologics pipeline. Responsibilities
Machine Learning Model Development: Design and fine‑tune deep learning and LLM‑based models (e.g., LLaMA 3.3, DiffDock, ProteinMPNN) for sequence–structure–activity prediction and optimization. Integrate antibody and protein‑specific biological knowledge into model architectures and training strategies. Antibody and Protein Therapeutic Design: Apply ML to support antibody humanization, CDR optimization, stability prediction, developability filtering, and manufacturability assessment. Collaborate with discovery teams to deploy AI‑driven workflows across antibody, multi‑specific, and cyclic peptide programs. Data Integration & Pipeline Ownership: Build robust pipelines for aggregating and structuring internal R&D data (sequences, 3D structures, binding data, developability attributes) for ML modeling; develop ETL systems and embedding workflows using LangChain, Milvus, or MariaDB Vector DB to support RAG‑based knowledge retrieval and protein annotation. Scientific and Cross‑Functional Leadership: Serve as the AI/ML technical lead on discovery programs, interfacing with computational biology, protein engineering, immunology, and bioinformatics teams; mentor junior team members and ensure reproducibility and traceability. Computing & Productionization: Scale model training and inference across GPU/HPC environments using frameworks like Dask, Ray, MPI, or AWS; integrate models and pipelines into scientific production environments (LIMS, R&D cloud platforms, etc.). Requirements
Ph.D. in Computational Biology, Computer Science, Bioinformatics, Structural Biology, or a related field. 5+ years of experience in AI/ML applied to protein or antibody drug discovery in an industry or translational research setting. Proven track record of developing and applying ML models for antibody/protein optimization, structure‑function modeling, or drug design. Proficient in Python and deep learning frameworks such as PyTorch or TensorFlow. Experience with LLMs, GNNs, and relevant tools for structure and sequence analysis (e.g., AlphaFold, Rosetta, DiffDock). Strong understanding of antibody engineering principles, therapeutic design challenges, and developability constraints. Demonstrated ability to work across disciplines and communicate complex ideas to cross‑functional teams. Preferred Qualifications
Experience building or leading AI/ML workflows embedded in therapeutic discovery pipelines. Familiarity with AI‑guided antibody design, cyclic peptides, or novel protein modalities. Prior exposure to IND or regulatory‑facing AI/data packages. Publication or speaking track record in ML for drug discovery or structural biology. Who This Role Is Not For
This is not a general AI/ML engineering role. Candidates without prior experience applying machine learning to therapeutic discovery, protein modeling, or antibody design will not be considered. We are specifically seeking scientists who have applied computational models in the biopharma or drug discovery setting, not those coming solely from academic ML, generic NLP, or unrelated AI fields. Compensation and Benefits
Base salary range: $150,000 – $200,000 annually. The final offer will be based on qualifications, experience, and skills. Typical offers will be mid‑point of the range, with higher compensation for exceptional candidates. Benefits include: 100 % paid employee medical, dental, and vision premiums. Short‑term and long‑term disability coverage. 401(k) plan with 50 % company match up to 3 %, vesting over 5 years. 15 paid days of PTO and sick leave; 11 paid holidays. Additional comprehensive benefits (details available upon request). SystImmune is an Equal Opportunity Employer. We welcome diverse talent and encourage all qualified applicants to apply.
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SystImmune is a leading and well‑funded clinical‑stage biopharmaceutical company located in Redmond, WA and Princeton, NJ, specializing in developing innovative cancer treatments using bi‑specific, multi‑specific antibodies and antibody‑drug conjugates (ADCs). We are seeking a highly skilled Senior or Principal Scientist with deep expertise in AI/ML and protein or antibody drug discovery to drive the design and implementation of advanced machine learning models and data infrastructure for our biologics pipeline. Responsibilities
Machine Learning Model Development: Design and fine‑tune deep learning and LLM‑based models (e.g., LLaMA 3.3, DiffDock, ProteinMPNN) for sequence–structure–activity prediction and optimization. Integrate antibody and protein‑specific biological knowledge into model architectures and training strategies. Antibody and Protein Therapeutic Design: Apply ML to support antibody humanization, CDR optimization, stability prediction, developability filtering, and manufacturability assessment. Collaborate with discovery teams to deploy AI‑driven workflows across antibody, multi‑specific, and cyclic peptide programs. Data Integration & Pipeline Ownership: Build robust pipelines for aggregating and structuring internal R&D data (sequences, 3D structures, binding data, developability attributes) for ML modeling; develop ETL systems and embedding workflows using LangChain, Milvus, or MariaDB Vector DB to support RAG‑based knowledge retrieval and protein annotation. Scientific and Cross‑Functional Leadership: Serve as the AI/ML technical lead on discovery programs, interfacing with computational biology, protein engineering, immunology, and bioinformatics teams; mentor junior team members and ensure reproducibility and traceability. Computing & Productionization: Scale model training and inference across GPU/HPC environments using frameworks like Dask, Ray, MPI, or AWS; integrate models and pipelines into scientific production environments (LIMS, R&D cloud platforms, etc.). Requirements
Ph.D. in Computational Biology, Computer Science, Bioinformatics, Structural Biology, or a related field. 5+ years of experience in AI/ML applied to protein or antibody drug discovery in an industry or translational research setting. Proven track record of developing and applying ML models for antibody/protein optimization, structure‑function modeling, or drug design. Proficient in Python and deep learning frameworks such as PyTorch or TensorFlow. Experience with LLMs, GNNs, and relevant tools for structure and sequence analysis (e.g., AlphaFold, Rosetta, DiffDock). Strong understanding of antibody engineering principles, therapeutic design challenges, and developability constraints. Demonstrated ability to work across disciplines and communicate complex ideas to cross‑functional teams. Preferred Qualifications
Experience building or leading AI/ML workflows embedded in therapeutic discovery pipelines. Familiarity with AI‑guided antibody design, cyclic peptides, or novel protein modalities. Prior exposure to IND or regulatory‑facing AI/data packages. Publication or speaking track record in ML for drug discovery or structural biology. Who This Role Is Not For
This is not a general AI/ML engineering role. Candidates without prior experience applying machine learning to therapeutic discovery, protein modeling, or antibody design will not be considered. We are specifically seeking scientists who have applied computational models in the biopharma or drug discovery setting, not those coming solely from academic ML, generic NLP, or unrelated AI fields. Compensation and Benefits
Base salary range: $150,000 – $200,000 annually. The final offer will be based on qualifications, experience, and skills. Typical offers will be mid‑point of the range, with higher compensation for exceptional candidates. Benefits include: 100 % paid employee medical, dental, and vision premiums. Short‑term and long‑term disability coverage. 401(k) plan with 50 % company match up to 3 %, vesting over 5 years. 15 paid days of PTO and sick leave; 11 paid holidays. Additional comprehensive benefits (details available upon request). SystImmune is an Equal Opportunity Employer. We welcome diverse talent and encourage all qualified applicants to apply.
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