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Strong Fortune-50 brand, metro location, mid-level ML role attracts high candidate density.
ML engineering skills are transferable across industries but legal domain specificity increases domain sensitivity slightly.
Explicit 2–5 years requirement and ML domain expertise create moderate shortlisting rigidity.
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Implement machine learning algorithms, manage model training and deployment for product applications.
Design data pipelines, write technical documentation, and contribute to AI innovation including patents and APIs.
Evaluate machine learning solutions, conduct case studies, design proofs of concept, and contribute to research for future development.
Bachelor's Degree preferred; relevant combination of coursework and experience may be considered.
2-5 years of relevant work experience.
Proficiency in Python, RESTful APIs, and secure data exchange patterns is necessary.
Experience with AI-assisted development tools, low-code solutions, and adherence to enterprise security, privacy, and data governance standards.
Experience building and supporting legal technology integrations such as contract lifecycle management and document management.
Operates well within agile teams, collaborating with legal, legal operations, and technology stakeholders to translate requirements into technical solutions.
Comfortable applying AI-assisted development using tools like GitHub and Microsoft Copilot, and continuously exploring emerging AI and legal technology advancements.