Principal Machine Learning Data Scientist, Gen AI
About the position Responsibilities • Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring the team follows industry standards in AI and ML development. • Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects and aligning them with Xometry's business objectives. • Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing, focusing on extracting structured data from technical drawings, purchasing orders, and other complex documents. • Lead the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models. • Design and implement efficient workflows for data preparation, cleaning, and augmentation to support the training of generative AI models. • Utilize cloud platforms (e.g., Amazon Web Services) for large-scale data processing, model training, and deployment. • Collaborate with cross-functional teams, including engineering and business teams, to align generative AI solutions with business needs and drive impactful applications. • Mentor and guide team members on advanced machine learning techniques, model architecture design, and problem-solving strategies to elevate the team's technical capabilities. • Continuously experiment and iterate on model performance, tuning architectures and parameters to improve accuracy and efficiency in a fast-paced, agile environment. • Stay updated with the latest research in generative AI, deep learning, and multimodal data processing, incorporating best practices and advancements into model development. Requirements • A bachelor's degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred. • 7+ years of experience in data science and machine learning, focusing on generative models, LLMs, or computer vision. • Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs). • Experience with multimodal data processing (e.g., combining text, image, and 3D data). • Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy. • Strong background in probability, statistics, and optimization techniques relevant to generative modeling. • Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker). • Familiar with software engineering principles, including version control, reproducibility, and continuous integration. • Experience in the manufacturing, supply chain, or similar industries is a plus. Apply tot his job