Senior Scientist, Bio AI

Earli tackles the #1 problem in the $100B cancer drug market: systemic toxicity. On-target/off-tumor effects force suboptimal dosing, reduced efficacy and sidelining some of the most potent drug classes such as cytokines. Earli’s BioAI approach flips this paradigm: Drugs are produced only where needed— in the tumor, by the tumor, against the tumor. Cancer cells become their own drug factories, enabling localized immune activation, even in cold tumors.

This was enabled by three core innovations:

Extrahepatic lipid nanoparticles (LNPs) that reach tumors such as lung cancer

AI-designed genetic switches that activate only in malignant cells by sensing transcription factor dysregulation

Local production of immune therapies (TCEs, cytokines, multispecifics) at the tumor site — “produce locally, consume locally”

Together, these technologies create a new biological control layer, allowing tumors to self-identify and trigger their own targeted immune attack—achieving specificity beyond current targeted or IO therapies.

Earli plans to enter the clinic by mid-2027 with a Phase 1/2 lung cancer trial. The company is backed by a16z, Khosla, Perceptive, Alex Gorsky, Marc Benioff, Breyer, Emerson Collective, Sands Capital and others. The SAB includes Jim Allison (Nobel Laureate, MD Anderson), Bob Langer (Co-founder Moderna, MIT), Phil Greenberg (Co-founder Juno), Amy Abernethy (frm. Principal Deputy FDA Commissioner), Bill Hait (former J&J EVP Oncology R&D), and Alan Ashworth (President UCSF Cancer Center). The leadership team brings deep gene therapy, LNP, CMC and tech experience; CEO Cyriac Roeding previously led a $250M (11x return) exit.

Who You Are

You share our same sense of dedication, scientific passion and entrepreneurial spirit

You work well in a fast-paced and extremely focused startup environment

You are not only smart, but clever and constantly think outside the box

You are able to make logical decisions in an instant when there is little time to evaluate

You are a natural communicator and relationship builder

You stay calm under high pressure and stress

You have the ability to multi-task in a serious way, with an extreme attention to detail

You become a representative of the core DNA of the company through who you are

The Position

Earli Inc. is currently seeking a top caliber Senior Scientist, Bio AI to join our Synthetic Bioengineering team.

Your Primary Responsibilities

Leverage cutting-edge ML, bioinformatics, and high-throughput assay data to design cancer-specific synthetic promoters and novel genetic medicines that will directly impact Earli’s clinical pipeline.

Train generative AI models for designing genetic medicines by leveraging Earli’s proprietary Massively Parallel Reporter Assay (MPRA) data as well as external data sets

Contribute to wet lab experimental design and data evaluation to benchmark AI model performance against ground truth wet lab data and create a rapid iteration loop

Perform routine computational analyses to analyze MPRA and other large experimental datasets using existing packages as well as bespoke analysis where needed. Provide accessible interfaces (e.g. Shiny apps) for routine data analysis (e.g. RNAseq profiling) for team members

Perform routine bioinformatic analyses on multi-modal omics data (RNAseq and scRNA-seq, ATAC-seq, proteomics, phospho-proteomics etc.) using individual as well as coherent multi-omic ML-based pipelines to identify key dysregulated targets and pathways in selected cancer indications

Routinely deploy code and execute on Earli’s infrastructure hosted by Cloud Service Providers (e.g. GCP) with appropriate engineering adaptations as needed. Help develop and work within budgets for GPU usage/compute

Your Required Experience, Knowledge and Skill

Master’s or PhD degree in a relevant field (bioengineering, computer science, data science, etc.) with a minimum of 3 years of hands-on experience using AI/ML applied to genomic/bioinformatic data using state-of-the-art GenAI models

Deep, direct expertise (preferably with high-quality publications) in developing novel GenAI models trained on massive biological data. Hands-on expertise in model training, fine-tuning, and in silico evaluation is a pre-requisite for this role.

An expert level of competence in data analysis on large and complex empirical data, such as MPRA data, multi-modal omics data, etc.

Familiarity with and prior experience collaborating with wet lab scientists to generate and curate high-throughput screening data on large libraries of DNA or RNA sequences

Proficiency in routine bioinformatic analyses such as differential gene expression, ATAC-seq and RNA-seq analysis, etc.

Expert level coding skills in Python and R

Basic knowledge of fundamental cancer biology is required. Deep expertise in cancer -omics, biomarkers, targets and pathways is preferred

Excellent verbal and written communication as well as interpersonal skills are required

Able to multi-task, manage multiple projects simultaneously and work effectively within a team

Ability to think independently and fully integrate into a high achieving team environment

The base salary for this position is $205,000-$235,000 per year.

If interested in applying, please attach a CV or have a well-developed LinkedIn profile for us to be able to assess your background.

We look forward to hearing from you!