Principal Engineer

Pull Logic is transforming the retail supply chain with a revolutionary availability-oriented paradigm that directly links customer preferences with real-time inventory. Backed by cutting-edge research from Georgia Tech’s School of Industrial and Systems Engineering, our AI-driven SaaS platform helps retailers and brands reduce lost sales, improve profitability, and elevate customer satisfaction. We’re looking for a Principal Engineer – Data Science/Machine Learning to join our core technology team. This is a unique opportunity to shape the foundation of Pull Logic’s enterprise-grade Retail Tech products and work on solutions that have a direct impact on how modern retailers operate. What You’ll Do - Own the end-to-end development of data science and machine learning solutions from problem definition and data exploration to production deployment and performance monitoring following clean coding practices and SOLID principles. - Architect and implement scalable data and ML systems, ensuring reliability, reproducibility, and low-latency model serving across Pull Logic’s platform. - Design and automate ML pipelines (data ingestion, feature engineering, training, validation, deployment) using modern MLOps tools and frameworks while maintaining adherence to object-oriented design and SOLID software architecture. - Prototype rapidly, test hypotheses, and iterate based on performance metrics and user feedback. - Lead technical design reviews and set best practices for data science engineering, experimentation, and ML deployment. - Contribute to the core data architecture, including data modeling, feature stores, and real-time data flows powering decision intelligence. - Mentor and guide other engineers and data scientists, fostering a culture of experimentation, continuous learning, and delivery excellence. - Partner with leadership to shape the long-term AI and data strategy, ensuring our ML systems scale with product and customer growth. What We’re Looking For - 7+ years of experience building and shipping data-driven products or Data Science-powered applications in fast-paced, high-growth environments - 3+ years of hands-on MLOps experience, owning the full lifecycle — from experimentation and feature engineering to production deployment and continuous model improvement - Strong command of Python and core data science libraries (Pandas, NumPy etc.), with the ability to write clean, modular, and testable code that adheres to SOLID principles - Deep understanding of software design patterns, APIs, and scalable data architectures for integrating ML into real-world systems - Proven ability to design, train, and deploy Data Science models and optimization algorithms that directly drive product features or business outcomes - Comfortable working across the entire data stack from pipelines and feature stores to inference APIs and monitoring - Solid grounding in statistics, optimization, and operations research, with a practical mindset for applying theory to solve business problems - Thrive in ambiguity, able to prototype quickly, validate ideas with data, and scale successful solutions - Excellent communicator who can collaborate with product, engineering, and leadership teams to align technical direction with business priorities - MS/MTech or PhD in Computer Science, Data Science, Industrial Engineering, or a related technical field (preferred but not required for exceptional candidates) Why Pull Logic? - Be part of a mission-driven company redefining supply chain intelligence for the retail world. - Work on cutting-edge technology with real-world impact and high visibility. - Collaborate with researchers and engineers from Georgia Tech, one of the top engineering schools in the world. - Grow with a dynamic, fast-paced team and play a key role in building the future of our platform. - Performance-based ESOP opportunities for exceptional contributors who help drive Pull Logic’s success and growth. Ready to Build What’s Next? Send your resume to careers@pulllogic.com and let’s start the conversation.