Role: Principal Engineer, ML (Computer Vision)
Nature of role: Full time - Hybrid - Dallas, TX & Richmond, VA
Essential Responsibilities:
• Help guide junior developers in computer vision and deep learning fundamentals such as feature extraction, CNNs, supervised machine learning, transfer learning and distributed deep learning.
• Serve as an engineering lead on various business delivery and engineering excellence initiatives.
• Suggest, collect, and translate requirements into an effective feature roadmap for organization platform capabilities.
• Evaluate and recommend tradeoffs of features to the platform that allow use case owners to refine output generation and new technology offerings in the space.
• Be a key partner in driving direction and goals for the team, both in terms of individual project impacts but also overall standards for machine learning and AI utilization in the organization.
• Guide teams in developing integration, end-to-end, and UAT test strategy as well as testing activities.
• Help drive the broader understanding of the use of machine learning and AI by interfacing with key roles in Operations, Legal, Security, and Technology.
• Stay on top of industry trends and best practices to continuously improve what we do and ensure our customer experience is the best it can be.
• Lead, mentor, and develop other engineers using technical expertise, best practices and industry standards for machine learning and AI systems.
Preferred Qualifications:
• Previous experience deploying large-scale applications on Azure.
• Familiarity with MLOps and industry-standard machine-learning Python libraries
• Experience with Azure AI services (Azure Machine Learning, Azure Cognitive Services)
• Advanced AI/ML specializations (reinforcement learning, deep learning, NLP)
• Proficient in an object-oriented programming language (i.e. C#, Java)
• 3+ years leading the end-to-end design and development of scalable services to be consumed by the enterprise, including monitoring and production support .
• 3+ years' experience building enterprise-level solutions with Microsoft Azure or equivalent cloud technologies .
• Experience with at least one major machine learning framework such as Tensorflow or PyTorch.
• Practical experience/theoretical understanding of developing and deploying computer vision deep learning models (e.g., CNN, Detectron, UNET, YOLO etc) at scale in production
• Experience in developing generative models such as diffusion models, GANs, and emerging methods