DatologyAI develops automated data selection tools that enable deep learning practitioners to train models on the most informative, high‑quality data. Leveraging proprietary, modality‑agnostic algorithms that detect redundancy, noise, and harmful samples without requiring labels, the company’s solutions span text, images, and beyond. By filtering out sub‑optimal data, DatologyAI helps organizations across industries reduce training costs while boosting model performance. The firm’s research‑driven approach and cross‑modal flexibility set it apart in the AI tooling market.
Open Positions
Technical Sourcer
4+ years of experience sourcing technical talent, excellent written communication, and comfortable using sourcing tools
Solutions Engineer (AI/ML, Pre-Sales)
4+ years of experience in software, ML platform, solutions, or customer engineering roles, with strong practical expertise in ML model training and demonstrated ability to design, run, and interpret model evaluations
Forward Deployed AI Engineer
5+ years of technical experience, strong background in distributed systems and data infrastructure, experience with ML/AI workflows and cloud platforms
Account Executive
5+ years of sales experience, experience selling into ML/AI, data, infra, or adjacent technical teams, thrive in early-stage environments
Product Marketing Manager
BS/MS in Computer Science, Engineering, or equivalent experience; 5+ years in technical marketing; deep expertise in machine learning
Research Scientist, Post-Training
3+ years of deep learning research experience, experience with post-training large vision, language, and multimodal models, and strong understanding of the fundamentals of deep learning
Software Engineer, Machine Learning Infrastructure
5+ years of experience, meaningful experience with leading and building production ML infrastructure, and strong knowledge of hardening cloud native and K8s workloads
Software Engineer, Data Infrastructure
5-10 years of experience in Data Engineering, including leading and building production data systems, building and managing scalable data processing solutions, and maintaining a high quality bar for design, correctness, and testing
Software Engineer, Infrastructure
Experience in large-scale infrastructure, proficiency in bash, Kubernetes, Python, and/or Terraform, and experience working with cloud platforms
Software Engineer Intern, Infrastructure
Pursuing a degree in Computer Science or related field, strong programming skills in Python, Go, or C++, and experience with Linux systems and cloud computing
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