Machine Learning Engineer

About PPLIED:PPLIED is a hands-free hiring platform designed to simplify and improve the job search and recruiting process for both employers and job seekers. Recruiters post a role once and receive a daily shortlist of top-matched candidates automatically, without the need for job boards, manual searching, or fees. Job seekers upload a resume once, and PPLIED continuously matches and applies to real roles on their behalf, eliminating repetitive applications and cover letters. When there is mutual interest, recruiters connect directly with candidates through the platform. PPLIED focuses on solving hiring challenges for both sides of the market in a streamlined, accessible, and free model.Note: This position is being promoted by PPLIED on behalf of one of our onboarded recruiters and hiring partners.Role Description:This full-time remote Machine Learning Engineer role focuses on building and maintaining the models that power PPLIED’s automated matching and recommendation engine. Day-to-day responsibilities include designing, training, and evaluating machine learning models related to candidate–role matching, ranking, and pattern detection across large-scale recruiting data. The role involves collaborating with product and engineering teams to translate business requirements into production-ready algorithms, integrating models into the platform’s backend services, and monitoring performance to ensure reliability and fairness. The Machine Learning Engineer will also work on data preprocessing pipelines, feature engineering, and experimentation, while contributing to continuous improvement of model accuracy, scalability, and bias mitigation.Qualifications:Strong foundation in Computer Science and Algorithms, including data structures and algorithmic problem-solving.Experience with Pattern Recognition and Neural Networks for real-world machine learning applications.Proficiency in Statistics for model evaluation, hypothesis testing, and performance analysis.Hands-on experience with machine learning frameworks and tools (e.g., Python, TensorFlow, PyTorch, scikit-learn).Background in designing and deploying production ML systems, including APIs and cloud-based infrastructure.Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience.Ability to work independently in a remote environment, communicate clearly with cross-functional teams, and document work thoroughly.Experience in recommender systems, search/ranking, or HR-tech platforms is a plus, as is familiarity with responsible AI and bias reduction techniques.