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C the Signs operates a GCP-native ML platform (Vertex AI, BigQuery, Kubernetes) designed to detect cancer across 100+ types in primary care settings. The engineering-heavy hiring focus and project backlog reveal the core challenge: moving from batch ML inference to low-latency clinical decision-making at scale. Active work on agentic workflows, LLM-as-a-judge validation, and observability suggests they're building toward real-time AI agents that can reason over patient data while navigating HIPAA/GDPR constraints—a significant operational lift beyond typical healthtech ML.
Tech Stack 82 technologies
Core StackVertex AI BigQuery Kubernetes LangChain Python RAG Scala Java AWS Apache Spark Apache Airflow TensorFlow PyTorch scikit-learn Pandas NumPy React TypeScript JavaScript Vertex AI Vector Search Cloud Run LangGraph Dialogflow CX GCP Azure FHIR HL7 DeepSpeed Ray Hugging Face Accelerate+52 more
What C the Signs Is Building
◆Challenges
- Hipaa/gdpr compliance for ai operations
- Low-latency inference and high availability
- Low-latency inference for clinical users
- Large diverse healthcare datasets
- Compliance with hipaa
- Scaling platform for new markets
- Ensuring platform quality across touchpoints
- Transforming passive ai responses into active behaviors
- Scaling automated testing
- Pii masking and data governance
▲Active Projects
- Enterprise grounding implementation
- Agentic workflow design
- Agent deployment on vertex ai
- Llm-as-a-judge framework
- Scalable data pipelines for healthcare datasets
- Comprehensive test strategies for web and mobile applications
- Scalable automated testing frameworks for ui, api, integration testing
- Llm training data pipeline
- Observability stack enhancement
- Multi-modal data integration
Hiring Activity
35 roles · 20 in 30d
Department
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