Achira
Drug Discovery
CADD/ApplicationScientist
Neural analysis suggests this role is
optimal for Mid+ candidates.
“CADD / Application Scientist at Achira. Skills: CADD, Molecular simulation, Drug discovery. Shape training data strategy. Identify data sources”
Industry & Context.
What They're Looking For.
Must Have
CADD, Structure-based drug design, Computational chemistry, Medicinal chemistry collaboration, Drug discovery, Supporting external collaborations, Leading external collaborations, Intuition for protein-ligand binding, Intuition for ligand poses, Intuition for assay artifacts, Intuition for protonation / tautomer states, Intuition for waters, Intuition for cofactors, Intuition for ligand strain, Expert judgments from imperfect data, Identify relevant benchmarks, Identify relevant application ideas, Identify relevant partner case studies
Nice to Have
Curating protein-ligand affinity benchmarks, Running protein-ligand affinity benchmarks, Curating FEP benchmarks, Running FEP benchmarks, OpenFE, Full discovery arc experience, Target identification, Hit finding, Hit-to-lead, Lead optimization, Designing scientific case studies, Designing technical reports, Designing partner-facing demonstrations, ML-assisted drug discovery, Active learning, Synthetic data generation, Model evaluation for molecular systems
What You'll Do.
Shape training data strategy
Identify data sources
Own structure curation
Interpret model successes
Interpret model failures
Decide applications to pursue
Shape partner programs
Translate model capabilities
How You'll Work.
Team & Collaboration
Work with model teams; Work with training teams; Work with ML researchers; Work with simulation scientists; Work with platform teams; Collaborate with BD; Collaborate with leadership; Collaborate with pharma teams; Collaborate with biotech teams
Full Job Description
WHY ACHIRA At Achira, you will join a team of scientists, ML researchers, and engineers working together to move beyond the beaten path in drug discovery. We are developing physics-grounded models for molecular simulation that can make the chemical and biological systems behind drug discovery more learnable, predictable, and designable. You will be part of the journey from our first protein-ligand applications in potency and lead optimization toward a broader vision: bringing more of the wet lab in silico, from selectivity and ADMET to eventual de novo molecular design. You will work at the frontier of AI x chemistry in a well-funded, talent-dense organization that values rigor, speed, execution, ownership, and the shared urgency required to turn ambitious models into real scientific tools. ABOUT THE ROLE We are looking for CADD / Application Scientists who want to help define the next generation of computational drug discovery tools, not just operate the current one. You will be a scientific design partner for our model and training teams, bringing real discovery program experience into what we train on, what model behaviors matter, and which applications are worth building toward. As the models mature, you will also help bring these tools to pharma and biotech partners, shaping collaborations around problems where better molecular simulation could change real program decisions. WHAT YOU’LL DO - Shape training data strategy for our models: identify which experimental, structural, partner-accessible, and synthetic data sources are likely to improve affinity prediction, selectivity, generalization, and downstream drug discovery utility. - Own data and structure curation for high-value protein-ligand systems end-to-end: connect affinity measurements to assay context, prepare structures, assign protein and ligand states, review or generate poses, and label assumptions and uncertainty. - Work with model and training teams to interpret model successes and failures, separ
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