Machine Learning Engineer

Role overview Build machine learning capabilities for text mining, document understanding, and automation of contractual and legal content. This individual contributor position combines applied NLP research with hands-on model development and deployment, helping create more personalized and efficient customer experiences across a large-scale agreement platform.

Responsibilities - Investigate and evaluate NLP, machine learning, and deep learning techniques that can be applied to contractual and legal data. - Maintain and extend rule-based, supervised, and unsupervised language-processing methods. - Apply approaches such as named entity recognition, part-of-speech tagging, parsing, sentiment analysis, clustering, and text prediction. - Learn and work within the product architecture, software development lifecycle, codebase, and release-management processes. - Support and improve training-data maintenance and enrichment workflows. - Deploy models to production and collaborate with product management on meaningful, customer-agnostic success metrics.

Requirements - 5+ years designing, developing, deploying, and monitoring machine learning or deep learning solutions. - Experience with Python and tools such as PyTorch, TensorFlow, spaCy, scikit-learn, or equivalent frameworks. - Programming experience in Python, C#, Java, C/C++, or a comparable language. - Bachelor’s degree in computer science, physics, statistics, econometrics, operations research, applied mathematics, or a related computational field. - Understanding of training, validation, testing, precision and recall, bias-variance, and other core machine learning concepts. - Experience extracting, cleaning, and manipulating large, diverse structured and unstructured datasets.

Nice to have - Experience with sequence-based deep learning, modern large language models, or computer vision. - Interest in continuous learning and keeping pace with advances in machine learning. - Experience supporting language-agnostic contract clause recognition.

Benefits and work setup Hybrid role requiring access to an office, with a weekly in-office expectation of at least two days, subject to team and local requirements.