Senior Machine Learning Engineer

Company Description

WeLaunch engineers businesses for the AI era by building a portfolio of vertical AI systems that operate inside real companies before becoming standalone assets. Rather than acting as a traditional agency or software vendor, WeLaunch designs systems that perform end-to-end operational work, from customer acquisition through service delivery and payment. The company uses two motions: installing AI systems into existing businesses and launching AI-native companies with an AI engine at their core. These systems automate full business loops across industries such as fire protection, pest control, and legal services, driving measurable change within weeks. Having built the brain of these systems first, WeLaunch is now focused on expanding its portfolio of AI-driven businesses.

Role Description

This is a full-time remote role for a Senior Machine Learning Engineer. The Senior Machine Learning Engineer will design, build, and deploy production-grade ML models that power WeLaunch's vertical AI systems, focusing on automating operational workflows and decision-making loops. Responsibilities include developing and optimizing algorithms, training and evaluating neural networks, and applying pattern recognition and statistical methods to real-world business data. The role involves collaborating with product and engineering teams to translate business processes into ML pipelines, implementing robust data processing and feature engineering, and ensuring models are reliable, scalable, and maintainable in production. The Senior Machine Learning Engineer will also contribute to system architecture, conduct rigorous experimentation, and mentor other team members in best practices for machine learning and software engineering.

Qualifications

• Strong foundation in Computer Science and Algorithms, with experience designing scalable, production-ready systems.
• Proficiency in Pattern Recognition and Statistics, applying these skills to analyze complex datasets and improve model performance.
• Hands-on experience with Neural Networks, including building, training, tuning, and deploying deep learning models.
• Advanced programming skills in languages such as Python, along with experience in ML frameworks (e.g., TensorFlow, PyTorch) and data tools (e.g., SQL, Pandas).
• Experience deploying and monitoring ML models in production environments (e.g., cloud platforms, containerization, CI/CD pipelines).
• Ability to translate business processes and requirements into technical solutions, working closely with cross-functional teams.
• Prior experience in building end-to-end ML pipelines, including data ingestion, feature engineering, training, evaluation, and iteration.
• Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, or a related field, or equivalent practical experience.
• Strong communication skills, commitment to inclusive collaboration, and comfort working in a remote, fast-moving environment.