Bioinformatics Engineer - Biologics

QP Group; San Francisco (CA); Hybrid; USD 120,000 - 180,000; Full time

Job summary

QP Group in San Francisco is seeking a Bioinformatics Engineer to advance AI-assisted biologics discovery. You will build benchmark datasets from real antibody and protein programs and work with software engineers and biologists to test agent decision-making in therapeutic discovery.

You will apply variant ranking, enrichment analysis, and advancement prioritization to define agent performance in biologics data. Strong Python or R skills and biology background are essential.

Qualifications

• 2+ years hands-on experience in biologics discovery or development.
• Experience interpreting binding kinetics, biophysical data, or cell-based potency assays.
• Proficiency in Python and/or R for data analysis and visualization.

Responsibilities

• Develop ground-truth benchmark datasets from antibody and protein discovery programs.
• Evaluate how AI agents reason through biologics datasets.
• Rank variants, perform enrichment analysis, and prioritize advancements.

Skills

Biologics discovery experience

Data analysis

Tools

Python

R

Job description

As molecular data generation and frontier model intelligence continue to advance, new approaches to data analysis are needed across the biotech industry. Our client builds intelligent, high-performance AI agents for biological data analysis, supporting thousands of scientists across a large network of R&D labs, handling data from instrument to insight.

They're seeking a Bioinformatics Engineer to join their Biologics Drug Discovery team, working at the frontier of what AI can achieve in biology.

About the Role

You'll contribute to the technical approach for evaluating how AI agents reason through complex biologics therapeutics datasets. Working alongside software engineers and biologists, you'll build ground-truth benchmark datasets, drawn from real antibody and protein discovery programs, that rigorously test whether agents can perform the critical decision-making steps human scientists execute. Your hands-on expertise in variant ranking, enrichment analysis, and advancement prioritization will define how agent capability is measured in therapeutic discovery.

Requirements

• 2+ years of hands-on experience in biologics discovery or development (antibody engineering, protein engineering, or cell/molecular biology-driven target validation).
• Experience interpreting binding kinetics (SPR/BLI), biophysical stability data, and/or cell-based potency assays.
• Proficiency in Python and/or R for data analysis and visualization.
• Familiarity with at least one of: antibody optimization (CDR engineering, VH/VL pairing, variant screening); protein structure (AlphaFold, cryo-EM, docking); high-throughput antibody/binding screens; PK/PD modeling for biologics (target occupancy, half-life, clearance); or bioprocess/manufacturability constraints.

Nice-to-Have

Experience with immunogenicity risk assessment.

Hands-on work with potency assay design (ELISA, cell-based, biochemical).

CMC/GMP-adjacent knowledge.

Culture

The team values hard work and output over face time, a collaborative rather than competitive internal culture, and cross-domain learning across benches. Based in San Francisco with daily meals, snacks, and a range of team social activities.

Compensation & Logistics

• Contract-based role (1099/W8-BEN equivalent), full-time hours, no fixed end date.
• Fully performance-based pay in the $120K-$180K range, uncapped upside tied to output.
• Paid ramp period with full target earnings from day one.
• Remote (global), hybrid, or onsite in San Francisco (onsite preferred).
• Work authorization: OPT visa holders only (excluding STEM Extension).
• Candidates who meet the above and have proven management experience may be considered for more senior positions.

Interview Process

Fast-moving process, roughly 8-12 days from submission to offer: intro screen with a technical recruiter, take-home technical project, technical interview with a member of technical staff, culture interview with senior leadership (if applicable), then offer.