Machine Learning Engineer

<div class="content-intro"><p>We’re in an unbelievably exciting area of tech and are fundamentally reshaping the data storage industry. Here, you lead with innovative thinking, grow along with us, and join the smartest team in the industry.</p> <p>This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us.</p></div><p><strong>THE ROLE</strong></p> <p class="isSelectedEnd">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.</p> <p class="isSelectedEnd">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.</p> <p class="isSelectedEnd">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.</p> <p><strong>WHAT YOU'LL DO</strong></p> <ul> <li>Design and implement ML and deep learning models for discovery and classification use cases, including entity extraction and document classification.</li> <li>Integrate LLMs and ML models into products and automated workflows, delivering measurable improvements in quality and automation.</li> <li>Define model training strategies and collaborate on dataset requirements and design.</li> <li>Build and maintain end-to-end ML pipelines covering training, inference, evaluation, monitoring, and iterative model improvement.</li> <li>Optimize models and inference pipelines for production constraints, including latency, cost, throughput, and infrastructure efficiency.</li> <li>Deploy, operate, monitor, and improve ML systems in production environments.</li> <li>Translate business challenges into ML system designs and technical trade-offs.</li> <li>Contribute to architectural decisions and the technical direction of applied AI solutions.</li> <li style="font-weight: bold;"><strong>We are primarily an in-office environment and ther