Redwood City, CA
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.
Designs end-to-end experiences for a technical data curation platform used by ML engineers and researchers, including complex workflows, data visualizations, and onboarding. Requires 5+ years of digital product design experience, strong visual craft, and expertise in design systems and interaction design.
Owns the company’s field marketing program across conferences, executive and investor events, speaking engagements, and webinars. The role requires 3–6 years of end-to-end event experience, strong project and vendor management, budget ownership, and confidence working with senior stakeholders.
Communicates AI research and product work through technical storytelling, demos, video, launches, and an authentic presence on X. The role requires technical legitimacy, strong creator instincts, community engagement, and the ability to support founders and researchers.
First Marketing Manager building content-led, founder-driven marketing programs at an AI infrastructure startup. Owns content calendar, social media, events, executive dinners, and reporting.
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.
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.
Versatile designer owning visual communication and brand at an early-stage AI data curation startup. Handle marketing design, product UI, and brand assets in a high-ownership, in-office environment.
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.
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.
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.
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.
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.
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.
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.
Builds scalable data and ML infrastructure supporting multi-cloud and deployment models. Partners with founders and engineers on core platforms, tooling, and research features for reliable production systems.