Lead Scientist, Experimental Engine for Life Models

Socket.dev; Palo Alto (CA); On-site; USD 245,000 - 305,000; Full time

Benefits offered by this job

30 days vacation

Health insurance

401K with company match

Quarterly retreats

Monthly wellness benefit

Office visits budget (Berlin, Palo Alt

Learning budget

Onboarding buddy

Job summary

Inceptive in Palo Alto seeks an exceptional scientific leader to build the experimental engine that trains, tests, and improves models for medicine design.

You will integrate molecular biology, functional genomics, and automation with ML and translational biology to design scalable experiments, recruit a multidisciplinary team, and turn ambitious ideas into robust platforms across the US and Europe.

Qualifications

• Proven ability to lead scalable biological assay projects advancing therapeutic discovery.
• Strong understanding of how experimental design affects model learning.
• Excellent cross-disciplinary communication and data interpretation.

Responsibilities

• Define experimental strategy to close gaps in model understanding and therapeutic design performance.
• Design experiments to train and evaluate generative and predictive models, in collaboration with biologists and ML experts.
• Generate high-quality, model-ready data using scalable methods such as functional genomics, high-throughput screening, multi-omics, and phenotypic profiling.
• Integrate assay development, automation, data generation, analysis, and interpretation in a fast-paced, collaborative environment.
• Recruit and lead a multidisciplinary team of experimental scientists and technology builders.

Skills

Team leadership

Cross-disciplinary communication

Global collaboration

Travel readiness

In-person collaboration

Tools

Laboratory automation

Job description

Inceptive in Palo Alto seeks an exceptional scientific leader to build the experimental engine that trains, tests, and improves models for medicine design.

You will integrate molecular biology, functional genomics, and automation with ML and translational biology to design scalable experiments, recruit a multidisciplinary team, and turn ambitious ideas into robust platforms across the US and Europe.