Company Description Jobrion is a career-focused technology company that streamlines the job search and application process for professionals. The organization helps individuals identify relevant opportunities across multiple platforms, reducing the time spent on manual searching. Jobrion optimizes resumes for Applicant Tracking Systems (ATS) to increase candidate visibility with employers. By managing key parts of the application workflow, Jobrion enables job seekers to focus on interview preparation and securing their next role. The team is committed to building tools that make career advancement more efficient and accessible.
Role Description The ML Engineer III is a full-time, remote role responsible for designing, developing, and deploying machine learning models that power Jobrion’s core products. This role includes building scalable data pipelines, performing feature engineering, and training and evaluating models for tasks such as opportunity matching, resume optimization, and candidate ranking. The ML Engineer III will collaborate closely with software engineers, product managers, and data analysts to translate business requirements into robust ML solutions and integrate them into production systems. Day-to-day responsibilities involve experimenting with new algorithms, improving model performance, monitoring production models, and ensuring reliability, fairness, and transparency in deployed systems. The role also includes documenting workflows, participating in code reviews, and mentoring junior team members.
Qualifications

Strong foundation in Computer Science and Algorithms, including data structures, algorithmic complexity, and software engineering best practices.
Proficiency in Statistics and Pattern Recognition for designing, evaluating, and interpreting machine learning models and experiments.
Hands-on experience with Neural Networks, including deep learning frameworks, model training, tuning, and deployment.
Advanced programming skills in languages such as Python or Java, and familiarity with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Experience building and maintaining production-grade ML systems, including data pipelines, model serving, and monitoring.
Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and containerization/orchestration tools (e.g., Docker, Kubernetes) is beneficial.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience.
Ability to work effectively in a remote, cross-functional team environment, with clear communication and collaborative problem-solving skills.

ML Enginner III

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