Datology AI
AI data curation platform for training deep learning models
DatologyAI builds tools to automatically curate and optimize training datasets for deep learning models. They serve AI teams curating petabyte-scale data across modalities, identifying redundant or harmful data without labels. This enables faster training, better performance, and lower costs for high-performing models.
Research Engineer
As a Research Engineer, you will conduct and enable cutting-edge research, translating it into the core product pipeline. You will develop and improve state-of-the-art data curation strategies, accelerating research and ensuring product innovation.
Forward Deployed AI Engineer (Post-Sales)
Lead post-sales deployment and adoption of DatologyAI's data curation platform for enterprise customers. Act as technical owner for on-prem and hybrid AI/ML deployments across AWS, GCP, Azure, and Kubernetes.
Research Scientist
Research Scientist investigates training data interventions to improve deep learning model quality and behavior. Sources ideas from literature, conducts customer-grounded research, and collaborates with engineers to deliver impact. Requires 3+ years deep learning research and PyTorch proficiency.
Product Manager
Owns product strategy and roadmap for enterprise AI data curation platform, translating ML research into shippable features. Partners with research, engineering, and sales; requires 5+ years PM experience in AI/ML tooling and strong technical foundation in ML pipelines.
Software Engineer, Full-Stack
Build full-stack data curation products and internal tools for AI model training optimization, owning the full development lifecycle. Requires proficiency in JavaScript/TypeScript, React, Python, and experience delivering production full-stack initiatives.
Software Engineer, Cloud Infrastructure
Designs, builds, and operates scalable multi-cloud infrastructure powering ML training, inference, and data curation pipelines. Collaborates with teams on AWS-focused systems using Kubernetes and IaC tools like Terraform.
Solutions Engineer (AI/ML, Pre-Sales)
Leads pre-sales PoCs for AI/ML data curation platform, partnering with customer ML teams to design evaluations, demonstrate training efficiency gains, and communicate results to technical and executive audiences. Requires 4+ years in ML platforms with hands-on training and evaluation expertise.
Research Scientist, Post-Training
Leads research on post-training data curation for foundation models, designing algorithms to generate/improve instruction and preference datasets, and unifying pre/post-training optimization. Requires 3+ years deep learning research, post-training experience with vision/language/multimodal models, and PyTorch proficiency.
Software Engineer, Data Infrastructure
Builds and maintains scalable data processing pipelines and backend systems for a data curation platform that optimizes training data for ML models. Partners with researchers to integrate research capabilities, ensuring reliability and security for customer data.