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Child Mind Institute Tech Stack

Mental health nonprofit building AI evaluation frameworks for clinical research

Mental Health Care New York, NY 201–500 employees Founded 2009 Nonprofit
childmind.org LinkedIn

Child Mind Institute combines clinical mental health care with large-scale AI research infrastructure. The tech stack reveals a dual-track operation: healthcare-grade systems (HL7, FHIR, Workday, Sage Intacct) for operations and patient management, paired with ML-heavy tooling (PyTorch, TensorFlow, scikit-learn, Hugging Face) for AI evaluation. The active project list—centered on evaluation frameworks, real-time model monitoring, and translating therapy protocols into measurable criteria—signals a core institutional mission: validating AI systems for clinical mental health contexts, not just deploying them.

Tech Stack 34 technologies

Core StackPython Docker Kubernetes AWS Terraform MATLAB scikit-learn PyTorch TensorFlow Hugging Face Expensify Workday Monday.com Salesforce Pardot JavaScript TypeScript React Azure Tidyverse SciPy Polars spaCy NLTK HL7 FHIR JASPER SAGE Intacct Ripple Sage Intacct+4 more

What Child Mind Institute Is Building

◆Challenges

  • Validating ai systems in clinical research
  • Scaling multi-rater evaluation systems
  • Complex large-scale ai research initiatives
  • Measurement gaps
  • Lack of measurement standards
  • Scalable program evaluation
  • Improving accounting operations
  • Ensuring accurate financial reporting
  • Streamlining audit coordination
  • Capacity management

▲Active Projects

  • Summer program for children with adhd
  • Large-scale ai evaluation framework infrastructure
  • Real-time model evaluation and monitoring infrastructure
  • Ai evaluation research initiatives in mental health contexts
  • Translation of manualized therapeutic protocols into evaluation criteria
  • Ai evaluation framework implementation
  • Metadata standards for multi-rater evaluation
  • Large-scale ai research initiatives
  • Evaluation plans for school-based programs
  • Product-evaluation frameworks for hmtk, pptk, curious, mirror, kandoo

Hiring Activity

Accelerating25 roles · 15 in 30d

Department

Healthcare
12
Data
5
Research
2
Engineering
1
Executive
1
Finance
1
Security
1

Seniority

Senior
9
Mid
4
Intern
3
Manager
3
Director
2
Junior
1
Staff
1

Notable leadership hires: Applications Director

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About Child Mind Institute

Child Mind Institute is a national nonprofit mental health organization based in New York, serving children and families with ADHD, anxiety, OCD, depression, and related learning disorders. The organization operates both direct clinical care and research programs, with explicit focus on advancing the science of child development and making resources freely available. The tech footprint spans clinical operations (EHR-adjacent standards, financial management via Sage Intacct and Workday) and substantial data science infrastructure (Python, Kubernetes, AWS), reflecting a hybrid model where clinical services and research infrastructure reinforce each other. Current hiring is healthcare-heavy (12 open roles), with secondary demand in data and research, indicating operational scaling alongside new research initiatives.

HeadquartersNew York, NY
Company Size201–500 employees
Founded2009
Hiring MarketsUnited States

Frequently Asked Questions

What is Child Mind Institute's tech stack?

Core tools include Python, PyTorch, TensorFlow, and scikit-learn for ML research; Docker and Kubernetes for infrastructure; AWS and Azure for cloud compute; healthcare standards (HL7, FHIR); and enterprise platforms (Workday, Sage Intacct, Salesforce) for operations.

What is Child Mind Institute working on?

Primary focus: large-scale AI evaluation frameworks for mental health research, real-time model monitoring infrastructure, translating therapy protocols into evaluation criteria, and multi-rater evaluation systems for school-based and clinical programs.

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How this profile is built

Child Mind Institute's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.