Machine Learning Engineer II
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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. • 4+ years of experience in machine learning, focusing on data engineering and/or data science. • Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs). • 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. • Experience with multimodal data processing (e.g., combining text, image, and 3D data).
Responsibilities
• Design, build, and optimize machine learning models to enhance Xometry’s platform and business operations. • Analyze large datasets to extract meaningful patterns and insights. • Collaborate with cross-functional teams to integrate machine learning models into production systems. • Learn and apply best practices in model evaluation, performance tuning, and deployment. • Influence technical direction by identifying opportunities to improve modeling approaches, data quality, and system architecture. • Work across teams to ensure machine learning solutions are explainable, maintainable, and aligned with business goals. • Help bridge the gap between research and production, ensuring models perform just as well in the real world as they do in notebooks. • Gain exposure to cutting-edge machine learning frameworks, tools, and techniques used in the manufacturing industry.
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