Top Tech Jobs & Startup Jobs

Build and maintain ML infrastructure and data pipelines for clinical document processing, deploy and monitor ML/LLM systems, support evaluation and annotation workflows, create internal tooling (e.g., Streamlit), and automate ML workflows to improve reproducibility and reduce operational burden.

Own technical onboarding for new hospital customers: environment setup, configuration, data mapping, and integrations with EHRs and clinical systems. Build and debug integrations (HL7, FHIR, APIs), collaborate with hospital IT and product teams, produce implementation docs and runbooks, support post-go-live stabilization, and manage multiple concurrent implementations.

Build and evaluate applied NLP and LLM systems for clinical text (oncology). Develop prototypes and production components for extraction, RAG, prompts, fine-tuning, and evaluation. Collaborate with clinical data and evaluation teams, write tested Python code, analyze model failures, and improve model robustness and reliability.

Design, build, and deploy multi-step LLM/agent extraction pipelines to convert large oncology patient documents into structured JSON; define evaluation datasets, run precision/recall analyses, iterate via prompt engineering, fine-tuning, or rule-based fixes; collaborate with annotation, customer clinical/data science, and internal engineering teams to deliver and scale production pipelines under tight timelines.

Own production health and customer issue resolution across deployments: investigate and trace issues across EHR ingestion, processing pipelines, AI extraction services, and application layers; monitor systems and set up alerts; build runbooks and triage workflows; communicate status to clinical users; identify recurring problems and drive product/engineering fixes; train support engineers.

Lead the end-to-end people function for a fast-scaling US-India AI health startup: own talent acquisition, org design, cross-geo operating model, culture, compensation and HR foundations, coach leaders, and build HR systems to enable rapid, high-quality hiring and scalable growth.

Build and maintain backend services and cloud infrastructure across AWS and Azure, manage Kubernetes clusters and GPU model-serving nodes, own CI/CD and deployments, implement monitoring/observability, debug production issues end-to-end, and standardize deployment runbooks while working with offshore engineers and customer-hosted environments.

Own end-to-end onboarding and EMR-integrated go-lives for cancer centers: build and manage project plans, coordinate internal and customer teams (FDE, clinical, IT, security), track risks and KPIs, drive timely launches, and create repeatable playbooks and handoffs to steady-state operations.

Lead GTM strategy and operations: build and own a full-funnel roadmap, define KPIs, design and run outreach campaigns, consolidate GTM tooling, create scalable playbooks, and partner with sales, product, and leadership to grow pipeline and improve conversion.

Own adoption, training, and enablement of the Triomics platform at customer cancer centers. Design and deliver role-specific training, build reusable enablement assets, embed with clinical teams to map workflows, drive go-live support and steady-state adoption, surface customer needs to engineering and product, and help scale playbooks and measurement of adoption.