About the Company

1touch.io is a leader in data discovery, AI enablement and sensitive data intelligence, helping enterprises automatically identify, map, and protect sensitive data across structured and unstructured systems. Our technology combines AI, automation, and deep data visibility to solve some of the toughest challenges in privacy, security, and governance.

About the Job

Our Machine Learning Engineer / Applied AI Engineer designs, builds, and deploys production-ready AI systems that transform business requirements into scalable, reliable, and high-quality machine learning solutions.

This role owns the full lifecycle of ML and LLM-based solutions — from problem formulation and model training to optimization, to deployment, and continuous improvement in production. The focus is on NLP, entity extraction, document classification, and LLM-powered automation across multiple business domains.

Responsibilities

Own the design and implementation of ML and DL models for discovery and classification use cases such as entity extraction and document classification
Integrate LLMs and ML models into products and automated workflows, ensuring measurable improvements in quality and automation
Define model training strategies and collaborate on defining dataset requirements and dataset design
Build and maintain end-to-end ML pipelines covering training, inference, evaluation, and iterative model improvement
Optimize models and inference pipelines for production constraints (latency, cost, throughput, infrastructure)
Deploy, operate, and iterate on ML systems in production environments
Translate business problems into ML system designs and technical trade-offs
Contribute to architectural decisions and technical direction of applied AI solutions

Requirements

Proven experience in shipping machine learning models to production and maintaining / improving them over time
Strong hands-on background in developing NLP and text-based ML systems including LLM-assisted workflows
Strong proficiency in Python and ML frameworks (PyTorch, Hugging Face Transformers, spaCy, etc.), with the ability to implement algorithms from first principles when needed
Experience implementing ML pipelines to automate model training, evaluation, monitoring and iterative improvement
Ability to design clean, modular, and testable ML code in a collaborative environment
Experience collaborating with software engineers, product managers, and business stakeholders
Strong communication skills and ability to explain ML concepts and system behaviour clearly