Senior/Staff AI Scientist, Antibody Design
Absci
August 24, 2026
Remote friendly (United States)
United States
$160,000 - $260,000 USD yearly
Clinical Research and Development
Responsibilities:
- Partner across AI Research, AI Engineering, Computational Biology, and Protein Engineering to advance protein design models for antibody drug design.
- Develop novel test-time compute strategies to maximize quality and efficiency of design pipelines.
- Perform multi-objective optimization of therapeutic design goals.
- Solve per-target design specification challenges via innovative AI-driven solutions.
- Analyze in silico and in vitro validation results to iteratively improve design and evaluation methodologies.
- Develop, deliver, and publish high-impact research in AI antibody design.
- Ensure work is accessible and interpretable to scientists with other domain expertise.
- Learn new technical skills to improve scientific contributions.
Qualifications:
- 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 (ideally 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 collaborate in an ambitious, fast-paced, interdisciplinary environment.
- Ability to present complex technical work to diverse audiences.
- Strong publication record in high-impact journals and conferences.
Skills/Tools (required):
- Deep learning; protein design and engineering; drug discovery; (background in) NLP, computer vision, and molecular dynamics.
Compensation Range:
- $160K - $260K
Application Instructions:
- Remote position with option to work onsite in NYC or Vancouver, WA if within commuting distance.
- Partner across AI Research, AI Engineering, Computational Biology, and Protein Engineering to advance protein design models for antibody drug design.
- Develop novel test-time compute strategies to maximize quality and efficiency of design pipelines.
- Perform multi-objective optimization of therapeutic design goals.
- Solve per-target design specification challenges via innovative AI-driven solutions.
- Analyze in silico and in vitro validation results to iteratively improve design and evaluation methodologies.
- Develop, deliver, and publish high-impact research in AI antibody design.
- Ensure work is accessible and interpretable to scientists with other domain expertise.
- Learn new technical skills to improve scientific contributions.
Qualifications:
- 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 (ideally 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 collaborate in an ambitious, fast-paced, interdisciplinary environment.
- Ability to present complex technical work to diverse audiences.
- Strong publication record in high-impact journals and conferences.
Skills/Tools (required):
- Deep learning; protein design and engineering; drug discovery; (background in) NLP, computer vision, and molecular dynamics.
Compensation Range:
- $160K - $260K
Application Instructions:
- Remote position with option to work onsite in NYC or Vancouver, WA if within commuting distance.