
1Cell.Ai delivers AI-driven diagnostics for cancer at the single-cell level. It focuses on precision oncology using circulating tumor cell–based, single-cell multi-omics lab-developed tests for…

1Cell.Ai delivers AI-driven diagnostics for cancer at the single-cell level. It focuses on precision oncology using circulating tumor cell–based, single-cell multi-omics lab-developed tests for…
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Company Description
1Cell.Ai Inc. is a leader in precision oncology, specializing in the development of cutting-edge Circulating Tumor Cell (CTC)-based single-cell multi-omics tests. These tests are instrumental in advancing clinical cancer care and supporting early-stage clinical trials for biotech and pharmaceutical companies. The company is a Silicon Valley-based company focused on multi-omics biomarker data analytics. By combining innovation in diagnostics and technology, 1Cell.Ai is a trailblazer in transforming oncology research and healthcare.
Role Description
The role involves developing end-to-end multimodal AI pipelines integrating:
• Digital pathology imaging
• Radiology imaging
• Molecular biomarker data
• Clinical structured data
• LLM-based knowledge systems
These pipelines support advanced applications including:
• AI-assisted biomarker quantification
• Multimodal biomarker discovery platforms
• Radiology + pathology multimodal analysis
• AI-assisted drug recommendation systems using LLMs
Key Responsibilities:
• Develop multimodal AI pipelines integrating imaging, structured data, and language models.
• Build deep learning models using PyTorch, including:
• Vision Transformers (ViT)
• Transformer architectures
• Attention-based models
• Multiple Instance Learning (MIL)
• Develop Generative AI workflows integrating imaging, clinical data, and LLM-based reasoning modules.
• Work on end-to-end AI workflows, including:
• Data preprocessing and quality control
• Feature engineering
• Model training and fine-tuning
• Validation and performance optimization
• Perform exploratory data analysis (EDA) using dimensionality reduction techniques such as: UMAP,
PCA, t-SNE.
• Implement model validation strategies, including:
ROC / AUC evaluation
• Sensitivity / specificity analysis
• Cross-validation
• Build AI pipelines for applications such as:
• Digital pathology image analysis
• Radiology imaging analytics
• Multimodal biomarker prediction
• AI-driven drug recommendation systems
• Maintain clean and reproducible codebases using GitHub version contro
Qualifications
• BE / B.Tech OR M.Tech/ MS - Computer Science, Artificial Intelligence & Machine Learning, Data
Science, Information Science, Statistics / Applied Mathematics
Key Skills
Strong experience in:
• Python programming for AI/ML
• PyTorch deep learning framework
• Transformer architectures
• Vision transformers
• Attention mechanisms
• Multiple Instance Learning (MIL)
• Multimodal AI pipelines
Good understanding of:
• Machine learning fundamentals
• Statistics and probability
• Model evaluation metrics
• Data preprocessing pipelines
Tools: Git / GitHub, VS Code, Docker / containerization
Preferred Skills (Nice to Have)
• Experience working with digital pathology or radiology imaging datasets
• Exposure to healthcare or oncology AI applications
• Experience building multimodal AI models combining imaging, text, and structured data
• Familiarity with LLM-based pipelines and GenAI systems
• Experience with cloud infrastructure (AWS / GCP / Azure)