EPM Scientific
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$180,000.00/yr - $250,000.00/yr Direct message the job poster from EPM Scientific Vice President - Preclinical Research Recruitment at EPM Scientific
A longevity-focused start-up stealth company is aiming to create a new "higher" level of human species — one capable of a drastically longer health span, superior intelligence, and seamless connection to digital intelligence. We believe this is the most important event in human history over the last 10 million years. The leap to this new level of humanity will be greater than the evolutionary jump from apes to hominids. Job Description This team is building a new software tool that conducts AI analysis of big data to find membrane surface proteins of pathological aging and cancer cells and enables spatial visualization regarding the degree of aging and cancer. The team already has raw single-cell RNA sequencing data for various organs and chronic diseases, with cells labeled as p16⁺ (senescent marker positive) or p16⁻ (negative), including gene expression profiles that cover identity markers and disease-related genes. This allows us to compare cell-type-specific expression patterns between senescent and non-senescent cells across different organs and disease states, enabling mapping of senescence signatures and discovery of potential therapeutic targets. Skill Criteria Machine Learning / Deep Learning Engineering (Core)
Welcoming strong AI/ML candidates even without biology background. Skills: Classification, clustering, and anomaly detection of cell states Feature selection for biomarker identification Model explainability (e.g., SHAP, LIME) Ability to design and implement advanced mathematical/computational models inspired by publications such as: "A generative statistical model for molecular data" - Nature Methods, 2025 https://www.nature.com/articles/s41592-025-02772-6 Tools: Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow) AutoML frameworks Hugging Face for transformer models (e.g., BioBERT, ProtBERT) Skills: Scalable pipelines for high-dimensional genomic, imaging, and molecular datasets Database integration across heterogeneous sources (omics + clinical + imaging) Distributed computing for large-scale AI training Data Visualization / Frontend Integration Skills: Visualizing disease or aging severity at cellular/tissue level Tools: Plotly Dash, Streamlit, R Shiny Optional: React + D3 Bonus / Preferred Skills (Not mandatory, but highly desirable for candidates interested in AI + Biology) AI tool development for biology applications (e.g., molecular modeling, drug discovery) Bioinformatics workflows: Single-cell RNA-seq (scRNA-seq) and spatial transcriptomics analysis Familiarity with ontologies & databases (e.g., UniProt, Cell Surface Protein Atlas) Tools:
Scanpy, Seurat, Bioconductor, Cell Ranger Stock options will be granted at founding-level terms, depending on the skillset and commitment of the candidate. Seniority level
Entry level Employment type
Full-time Job function
Research and Science Industries
Pharmaceutical Manufacturing Referrals increase your chances of interviewing at EPM Scientific by 2x. Get notified about new Machine Learning Engineer jobs in
San Francisco County, CA .
#J-18808-Ljbffr
$180,000.00/yr - $250,000.00/yr Direct message the job poster from EPM Scientific Vice President - Preclinical Research Recruitment at EPM Scientific
A longevity-focused start-up stealth company is aiming to create a new "higher" level of human species — one capable of a drastically longer health span, superior intelligence, and seamless connection to digital intelligence. We believe this is the most important event in human history over the last 10 million years. The leap to this new level of humanity will be greater than the evolutionary jump from apes to hominids. Job Description This team is building a new software tool that conducts AI analysis of big data to find membrane surface proteins of pathological aging and cancer cells and enables spatial visualization regarding the degree of aging and cancer. The team already has raw single-cell RNA sequencing data for various organs and chronic diseases, with cells labeled as p16⁺ (senescent marker positive) or p16⁻ (negative), including gene expression profiles that cover identity markers and disease-related genes. This allows us to compare cell-type-specific expression patterns between senescent and non-senescent cells across different organs and disease states, enabling mapping of senescence signatures and discovery of potential therapeutic targets. Skill Criteria Machine Learning / Deep Learning Engineering (Core)
Welcoming strong AI/ML candidates even without biology background. Skills: Classification, clustering, and anomaly detection of cell states Feature selection for biomarker identification Model explainability (e.g., SHAP, LIME) Ability to design and implement advanced mathematical/computational models inspired by publications such as: "A generative statistical model for molecular data" - Nature Methods, 2025 https://www.nature.com/articles/s41592-025-02772-6 Tools: Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow) AutoML frameworks Hugging Face for transformer models (e.g., BioBERT, ProtBERT) Skills: Scalable pipelines for high-dimensional genomic, imaging, and molecular datasets Database integration across heterogeneous sources (omics + clinical + imaging) Distributed computing for large-scale AI training Data Visualization / Frontend Integration Skills: Visualizing disease or aging severity at cellular/tissue level Tools: Plotly Dash, Streamlit, R Shiny Optional: React + D3 Bonus / Preferred Skills (Not mandatory, but highly desirable for candidates interested in AI + Biology) AI tool development for biology applications (e.g., molecular modeling, drug discovery) Bioinformatics workflows: Single-cell RNA-seq (scRNA-seq) and spatial transcriptomics analysis Familiarity with ontologies & databases (e.g., UniProt, Cell Surface Protein Atlas) Tools:
Scanpy, Seurat, Bioconductor, Cell Ranger Stock options will be granted at founding-level terms, depending on the skillset and commitment of the candidate. Seniority level
Entry level Employment type
Full-time Job function
Research and Science Industries
Pharmaceutical Manufacturing Referrals increase your chances of interviewing at EPM Scientific by 2x. Get notified about new Machine Learning Engineer jobs in
San Francisco County, CA .
#J-18808-Ljbffr