Jobright is a next-generation AI job search platform built to make career navigation faster, smarter, and more personal. They are looking for a Machine Learning Engineer to design, train, and ship the models that power how our AI agents understand resumes, match jobs, and guide people through their careers.

Why Join Us

Build models that directly shape the career outcomes of millions of job seekers, not abstract benchmarks on a leaderboard Take ownership of the full ML lifecycle, from data and training to deployment, monitoring, and iteration Work alongside engineers and researchers who care about model quality, system design, and shipping speed in equal measure Join a team that invests in serious ML infrastructure, so you can spend your time on modeling instead of glue code

Responsibilities

Design, train, and deploy machine learning models that power core capabilities across the Jobright platform, including matching, ranking, and recommendation Build and maintain training pipelines, feature stores, and evaluation frameworks that make experimentation fast and results trustworthy Partner with product, engineering, and applied AI teammates to translate ambiguous product goals into well-defined modeling problems and shipped features Monitor model performance in production, diagnose regressions, and feed those learnings back into the next iteration

Qualifications

Required

Early-career engineer with 1 to 3 years of experience in machine learning, data science, or a closely related technical field Clear communicator who can explain modeling choices, tradeoffs, and results to both technical teammates and non-technical stakeholders Solid grounding in classical ML and modern deep learning, including the fundamentals of training, evaluation, and deploying models at scale

Preferred

Prior internship or industry experience in ML engineering, applied research, or data science at a tech or AI-focused organization Track record of shipping production ML systems in fast-moving environments where data, requirements, and priorities shift regularly Hands-on skills in Python, PyTorch or TensorFlow, distributed training and inference, MLOps tooling, and SQL-based data systems