Senior Scientist, Bio AI

Earli is a BioAI therapeutics firm in Redwood City, California that programs cancer to turn against itself. Cancer cells become hyperlocal factories for potent immune therapies that are otherwise too toxic to be used systemically . Earli AI-designs synthetic genetic switches that are intravenously injected but ONLY activate in cancer cells, using non-integrating DNA in a stealth LNP. Once activated, they force the cancer cells to produce encoded proteins – T cell engagers, cytokines, agonists – that activate the immune system to kill the cancer. The hyperlocal activation avoids on-target/off-tumor effects and drives up the therapeutic index. Instead of focusing on where the drug goes , Earli changes where the drug is produced . 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 interpersona