Senior Machine Learning Engineer

Role overview Develop and productionize machine learning solutions that improve the understanding, processing, and automation of contractual and legal content. This senior individual contributor role combines applied research, natural language processing, deep learning, model operations, and close partnership with product teams to create more personalized and automated customer experiences.

Responsibilities - Research, test, and evaluate established and emerging NLP, machine learning, and deep learning methods for document and contract data. - Extend rule-based, supervised, and unsupervised approaches for language understanding tasks. - Apply techniques such as named entity recognition, part-of-speech tagging, parsing, sentiment analysis, clustering, and text prediction. - Improve training-data maintenance, enrichment, and related model development processes. - Deploy, monitor, and improve models in production using current and emerging machine learning practices. - Work with product management to convert product needs into robust, customer-agnostic success metrics.

Requirements - 8+ years designing, developing, deploying, and monitoring machine learning or deep learning solutions. - Experience with Python and frameworks or libraries such as PyTorch, TensorFlow, spaCy, scikit-learn, or equivalents. - 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 similar computational discipline. - Strong understanding of machine learning concepts including training, validation, testing, precision and recall, and bias-variance considerations. - Experience extracting, cleaning, and manipulating large, varied structured and unstructured datasets.

Nice to have - Experience developing and deploying sequence-based deep learning models, modern language models, or computer vision systems. - Familiarity with current NLP model technologies and a commitment to staying current with industry developments. - Experience contributing to 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.