Bioinformatics Engineer - Oligonucleotide

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

Job summary

QP Group in San Francisco is seeking a Bioinformatics Engineer to join the Oligonucleotide Drug Discovery team, applying AI-driven analysis to design and evaluate therapeutics. You will build datasets and workflows across target validation, ASO/siRNA design, screening, and pharmacology, collaborating with software engineers, biologists, and drug hunters in a flexible, output-focused culture.

You will contribute to end-to-end workflows across instrument outputs, experimental readouts, and real

Qualifications

• 3+ years hands-on oligonucleotide/RNA therapeutics experience.
• Experience validating drug targets or MOA via functional or population genomics.
• Familiarity with drug discovery workflows, sequence design, knockdown screening, or preclinical PK/PD.
• Proficiency with AI agents/tools in a working capacity.

Responsibilities

• Contribute to end-to-end workflows for teaching AI agents to understand and handle complex drug discovery data.
• Build datasets and pipelines that enable AI-driven reasoning across target selection, ASO/siRNA design, screening and pharmacology.
• Collaborate with software engineers, biologists, and drug hunters to deliver robust analyses and insights.
• Support data generation from instrument outputs to actionable scientific decisions.

Skills

Oligonucleotide (ASO/siRNA) experience

RNA therapeutics

Drug target validation

AI tools proficiency

Tools

AI tools

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 Oligonucleotide 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 teaching AI agents to understand and handle complex drug discovery and development data, working across end-to-end workflows from instrument outputs and experimental readouts through to real scientific decisions. You'll work alongside software engineers, biologists, and drug hunters, building datasets that teach these agents to reason better across: genetic target and mechanism-of-action selection; ASO/siRNA drug design; screening and functional characterization; and pharmacology.

Requirements

• 3+ years of hands-on experience with oligonucleotide (ASO/siRNA), RNA therapeutics, or related modalities.


• Experience in drug target validation or mechanism-of-action studies using functional or population genomics.


• Familiarity with drug discovery and development workflows, sequence design, knockdown screening, or preclinical PK/PD.


• Proficiency using AI agents/tools in a working capacity.

Culture

Flexible working hours, with the expectation that you communicate if coming in later than usual. The team values hard work and output over face time, a collaborative rather than competitive internal culture, and cross-domain learning across benches. With daily meals, snacks, and a range of team social activities (sports clubs, outings, offsites).

Compensation & Logistics

• Contract-based role (1099/W8-BEN equivalent), full-time hours, no fixed end date.


• Fully output-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.