Senior/Staff AI Scientist, Antibody Design

🕒 August 21

☕ Washington – Remote

☕ Washington – Remote

💵 $160k - $260k / year

⏰ Full Time

🟠 Senior

🧠 AI Research Scientist

👻 Ghost score 19%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Absci

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2011

🧬 Biotechnology

🤖 Artificial Intelligence

💊 Pharmaceuticals

Biotechnology • Artificial Intelligence • Pharmaceuticals

Absci is a biotechnology company that uses generative artificial intelligence together with wet-lab validation to design de novo biologics, primarily antibodies. Its integrated AI Drug Creation Platform performs data generation, model training, de novo design, multi-parametric lead optimization, and AI-enabled target discovery (using reverse immunology) to uncover novel antibody/target pairs and accelerate IND-enabling studies. Absci advances internal and partnered therapeutic programs—such as ABS-201, a designed antibody targeting prolactin receptors for androgenetic alopecia—and emphasizes rapid iterative cycles between AI and lab work to shorten biologics discovery timelines.

📋 Description

• Advance and deploy protein design models for antibody drug design • Apply expertise across deep learning, protein design and engineering, drug discovery, natural language processing, computer vision, and molecular dynamics • Develop innovative approaches to creating and assessing therapeutic antibodies in silico • Develop novel machine learning models and apply them to identify novel targets and generate candidate antibody therapeutics • Partner with AI Research, AI Engineering, Computational Biology, and Protein Engineering teams • Develop test-time compute strategies to maximize design-pipeline quality and efficiency • Perform multi-objective optimization of therapeutic design goals • Solve per-target design specification challenges with AI-driven solutions • Analyze in silico and in vitro validation results to improve design and evaluation methodologies • Develop, deliver, and publish high-impact research • Ensure work is accessible and interpretable to scientists in other domains • Learn new technical skills to improve scientific contributions

🎯 Requirements

• PhD or equivalent experience in Machine Learning, Computer Science, Computational Biology, Computational Chemistry, Biophysics, or a related field • 3+ years of research experience at the intersection of machine learning and protein design, molecular modeling, or a related field, ideally including industry experience • Fluency in Python and PyTorch • Experience designing, implementing, and evaluating state-of-the-art AI algorithms for protein design and protein structure prediction • Ability to work collaboratively in an ambitious, fast-paced, interdisciplinary environment • Experience presenting complex technical work to diverse audiences • Strong publication record in respected, high-impact journals and conferences • Legal authorization to work in the United States

🏖️ Benefits

• Equity • Bonus • Access to industry-leading compute resources • Access to Absci’s Wet Lab for rapid design > build > test > learn cycles • Opportunity to see work translated into therapeutic impact for patients • Remote work, with option to work onsite at the New York City office or Vancouver, WA headquarters if within commuting distance