AI Biologist - Biologics Development

LatchBio • San Francisco, CA

11h • $120,000 - $180,000

About The Position

Latch builds scientific benchmarks for AI agents across biology, working with frontier labs and pharmaceutical companies to evaluate performance on real biological workflows. The AI Biologist will join the TxBench team and help assess AI capabilities in therapeutic antibody development.

The role serves as the scientific authority for ground truth, evaluating whether AI agents can reason like expert biologics development scientists. The benchmark covers monoclonal antibodies, Fc-fusions, and bispecifics between lead nomination and IND. The role works with software engineers and scientists to build benchmark tasks and datasets, and sets standards for agent outputs and decisions.

The work includes converting development workflows into file-based tasks with structured outputs and deterministic grading; creating gold-standard answers and curated data fixtures; evaluating difficult scientific judgments, including distinguishing genuine liabilities from analytical artifacts; and reviewing agent reasoning, identifying errors, assessing confidence, and communicating what evidence would change a conclusion.

The position is a full-time 1099 contract (or W-8BEN internationally) with no stated end date. Pay is guaranteed during weeks 1–4 of ramp-up and then paid per certified task. Most people in the position earn $120,000–$180,000 or more, with uncapped upside. Work is on the employee’s own schedule, and most of the team works 40 or more hours per week. The role may be remote, hybrid, or onsite in San Francisco; onsite is preferred. Onsite perks include catered lunch and dinner daily, a waterfront Mission Bay office, and monthly parking when available.

Requirements

• PhD in protein engineering, biochemistry, analytical chemistry, pharmacology, or a related field.
• Hands-on experience analyzing antibody development data; the candidate must have performed the analysis rather than only supervised it.
• Deep expertise in at least one of analytical/CMC characterization, large-molecule DMPK, protein engineering and developability, or non-clinical safety, with working fluency across the other areas.
• Command of how readouts map to critical quality attributes, PK and effector properties, and release or comparability decisions.
• Python or R skills for data analysis, including parsing chromatograms and electropherograms, kinetic fitting, or PK modeling.
• Daily use of Claude, Cursor, or similar AI agents, and judgment to recognize reasoning that is technically correct but scientifically unsound.
• Confidence to overrule an AI agent when evidence demands it and openness to update when shown wrong.
• Ability to calibrate confidence and communicate uncertainty rather than defaulting to binary calls.

Nice To Haves

• Antibody format and Fc engineering experience, including IgG subclasses, YTE/LS, effector-silencing, or bispecific architectures.
• Familiarity with MAM, ICH Q6B/Q5E, FDA immunogenicity guidance, IMGT, SAbDab, and IEDB.

Responsibilities

• Turn real biologics development workflows into file-based tasks with structured outputs and deterministic grading, covering developability triage, analytical/CMC characterization, PK and FcRn reasoning, immunogenicity, effector function and safety, and first-in-human dose projection.
• Write gold-standard answers from raw data, using tolerances that account for replicate, integration, and fitting variability.
• Curate data fixtures including developability panels, glycan LC-MS, charge-variant CE, intact/subunit MS, SEC-MALS, FcRn/FcγR sensorgrams, concentration-time PK, and immunogenicity and effector assays.
• Partner with software engineers to translate scientific judgment into new workflows.
• Test whether agents distinguish real liabilities from analytical artifacts and whether conclusions are supported by orthogonal evidence.
• Evaluate whether agents match effector function and affinity to mechanism, distinguish linear from target-mediated clearance, and assess molecules against their target product profiles.
• Interrogate agent reasoning step by step and challenge conclusions that would not withstand development review or a go/no-go decision.
• Identify why agents fail, what an expert would do instead, and what evidence would change a call.
• Score agent confidence and reward explicit uncertainty over overconfident conclusions.

Benefits

• Pay guaranteed for weeks 1–4 while ramping.
• Uncapped earning upside through per-certified-task pay.
• Flexible scheduling; the worker decides how to structure their work time.
• Remote, hybrid, or onsite work options.
• Catered lunch and dinner daily for onsite staff.
• Waterfront office in Mission Bay.
• Monthly parking when available.
• Company outings most months, team off-sites, and activities including a run club, cycling, boxing, ice skating, and soccer.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree