remote
Lead Machine Learning Engineer - LexisNexis
ML Engineer
Lead a team of ML engineers to design, develop, and deploy generative AI and NLP solutions for legal analytics, leveraging Python, deep learning frameworks, and cloud services.
About the role
Key Responsibilities
- Architect and implement end‑to‑end machine‑learning pipelines for generative AI and natural‑language processing applications in the legal domain.
- Lead a multidisciplinary team, providing technical guidance, code reviews, and mentorship to ensure high‑quality, production‑ready models.
- Collaborate with product managers, data scientists, and legal experts to translate business requirements into scalable AI solutions.
- Design, train, and optimize deep‑learning models using TensorFlow or PyTorch, focusing on accuracy, latency, and interpretability.
- Deploy and monitor models on AWS (SageMaker, EC2, Lambda) ensuring reliability, security, and compliance with ethical AI standards.
Requirements
- 5+ years of professional experience in machine learning, with at least 2 years in a leadership or lead engineer role.
- Strong proficiency in Python and deep‑learning frameworks such as TensorFlow or PyTorch.
- Hands‑on experience building and deploying NLP or generative AI models at scale, preferably in cloud environments (AWS).
- Solid understanding of data engineering concepts, model versioning, CI/CD for ML, and performance monitoring.
- Excellent problem‑solving skills, ability to communicate complex technical concepts to non‑technical stakeholders, and a commitment to ethical AI practices.
Skills
pythontensorflowpytorchawsnatural language processingdeep learning