Software Engineer II

We are looking for a Machine Learning Engineer who will be responsible for improving and maintaining our machine learning models/pipelines, developing scalable ETL pipelines, and optimizing the end-to-end data processing workflow. This role requires strong experience in computer vision, OCR, and deep learning, as well as the ability to deploy models in a production environment.

Responsibilities:

• Design, develop, and maintain data pipelines to manage TIFF images, extracted fields, CSV, PDF, XML, and structured outputs.
• Build and optimize ETL workflows for preprocessing (resizing, rotation, denoising) and ML pipeline integration.
• Develop, train, evaluate, deploy, and monitor deep learning models in a production environment.
• Develop API endpoints and integrate structured data into the existing data keying application.
• Implement logging, monitoring, and error-handling mechanisms for model performance and data consistency.
• Work with Dockerized deployments to streamline ML and data workflows.
• Collaborate with ML engineers, software developers, and quality test engineers to ensure seamless integration.

Qualifications:

• Bachelor's Degree holder.
• 3+ years of experience in data engineering, ML engineering, or a hybrid role.
• Proficiency in Python for data manipulation, API development, and ML integration.
• Ability to write efficient ETL scripts and manage large datasets.
• Strong knowledge of database management (SQL, NoSQL, PostgreSQL, or similar).
• Familiarity with YOLO-based object detection and OCR processing.
• Knowledge of image processing and computer vision tools such as Pillow, OpenCV, pdf2image, etc.
• Experience with training and testing machine learning models using Tensorflow, Pyspark, and Scikit-learn.
• Hands-on experience with Docker, Kubernetes, and containerized ML workflows.
• Experience working with Azure services (Data Factory, Blob Storage, ML Studio, and other compute resources).
• Experience with Flask, FastAPI, or other API frameworks.
• Knowledge of MLOps best practices for deploying and monitoring ML models in production.
• Hands-on experience using Git and Github/Gitlab, and Github Actions.

Preferred Skills (Nice to Have):

• Experience working in insurance, document processing, or OCR-related applications.
• Knowledge of distributed data processing (Spark, Dask, or similar).
• Exposure to DevOps practices for CI/CD pipelines in ML projects.
• Familiarity with NLP and LLM-based models.

LexisNexis, a division of RELX, is an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form: https://forms.office.com/r/eVgFxjLmAK , or please contact 1-855-833-5120.

Please read our Candidate Privacy Policy.