Job Description
We are seeking a Deep Learning Engineer with experience manipulating large 2D and 3D media datasets. In this role, you will implement core algorithms that sit at the intersection of computer vision and computer graphics, helping us turn high dimensional data into high-fidelity content. Key Responsibilities Algorithm Implementation: Implement core deep-learning, computer vision, and (inverse-)procedural modeling algorithms in Python. You will rely on mathematical techniques from linear algebra, probability, and geometry to build these systems. Applied Research: Apply cutting-edge research in machine learning and computer graphics to solve real-world problems. Cross-Functional Coordination: Work closely with our cofounders to understand high-level product vision and translate customer requirements into technical milestones. Scaling & Deployment: Interact with remote machines via a Unix shell to deploy and test code on large-scale geospatial datasets, ultimately generating 3D content for our customers. Code Management: Use Git to manage source code and modularize complex implementation tasks into manageable, executable components. Master's degree in Computer Science, Engineering, Mathematics, or a related field 3+ years of relevant industry experience in a fast paced, high growth tech environment. Professional Experience: Proven experience as a DL Engineer or Applied Research Engineer in a fast-paced environment. Industry Context: Prior experience in industries with complex multi-disciplinary teams such as robotics, smart grids, precision agriculture, game development, or aerospace is highly valued. Technical Proficiency: Core Stack: Fluency with Python, Git, and the Unix shell. ML Experience: Proven experience training and debugging artificial neural networks or adjacent experience (e.g., gradient descent, nonlinear optimization, or classical machine learning). Math Foundations: A strong mathematical background covering linear algebra, statistics, probability, and num
