Machine Learning Engineer

THE ROLE

1touch.io is a technology company focused on automated, real-time discovery, mapping, and tracking of sensitive personal data. Its AI-powered platform helps enterprises improve data privacy, security, and governance across complex on-premises and cloud environments.

Together, 1touch.io and Everpure transform enterprise data from passive storage into an intelligent, context-aware, and governed foundation - making it AI-ready at the source so organizations can securely understand, trust, and activate their data at scale.

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

WHAT YOU'LL DO

• Design and implement ML and deep learning models for discovery and classification use cases, including entity extraction and document classification.
• Integrate LLMs and ML models into products and automated workflows, delivering measurable improvements in quality and automation.
• Define model training strategies and collaborate on dataset requirements and design.
• Build and maintain end-to-end ML pipelines covering training, inference, evaluation, monitoring, and iterative model improvement.
• Optimize models and inference pipelines for production constraints, including latency, cost, throughput, and infrastructure efficiency.
• Deploy, operate, monitor, and improve ML systems in production environments.
• Translate business challenges into ML system designs and technical trade-offs.
• Contribute to architectural decisions and the technical direction of applied AI solutions.

WHAT YOU BRING

• Experience delivering machine learning models into production and improving them over time.
• Hands-on experience developing NLP and text-based machine learning systems, including LLM-assisted workflows.
• Proficiency in Python and machine learning frameworks such as PyTorch, Hugging Face Transformers, spaCy, or similar.
• Experience implementing ML pipelines to support model training, evaluation, monitoring, deployment, and continuous improvement.
• Ability to design clean, modular, and maintainable ML solutions in a collaborative environment.
• Experience collaborating with software engineers, product managers, and business stakeholders.
• Strong communication skills and the ability to explain machine learning concepts and system behavior clearly.