AI/ML 3D Deep Learning Engineer (Avadi)

Role Overview: As a Deep Learning Engineer specialized in 3D Computer Vision and Reinforcement Learning, you will be responsible for developing, implementing, and optimizing state-of-the-art models that address complex challenges in spatial AI and geometric processing. You will play a key role in a multidisciplinary team dedicated to pushing the boundaries of 3D representation, algorithmic generation, and autonomous agents, ultimately contributing to the research, development, and deployment of large-scale AI systems capable of interpreting, manipulating, and generating intricate 3D structures. Key Responsibilities: - Develop, implement, and optimize advanced deep learning models focusing on Computer Vision, 3D CNNs, and Geometric Deep Learning. - Design custom neural network architectures and autonomous agents for interacting with, interpreting, and generating complex 3D geometries, including CAD data and 3D meshes. - Lead and contribute to research initiatives centered around advanced deep learning models, particularly 3D Convolutional Neural Networks (CNNs), Geometric Deep Learning, and Deep Reinforcement Learning (DRL) for spatial problem-solving. - Conduct training and fine-tuning of complex models (e.g., DRL agents, 3D CNNs) in simulated and geometric environments using modern machine learning frameworks such as PyTorch and TensorFlow. - Work on scaling, optimizing, and enhancing the efficiency of custom algorithms and large models, including distributed training, parallelism, and hardware acceleration (GPUs, TPUs). - Collaborate with engineering teams to integrate 3D deep learning models and agentic workflows into robust, scalable production systems. Qualifications Required: - 1 to 4 years of relevant experience in developing deep learning models. - Degree in Computer Science, Applied Mathematics, Artificial Intelligence, or a related discipline. - Specialized coursework or research in 3D deep learning, reinforcement learning, and advanced algorithmic design. - Strong mathematical foundation. - Expertise in deep learning and machine learning algorithms, particularly in the context of 3D vision, reinforcement learning, and generative geometric models. - Proficiency in programming languages like Python and C++. - Familiarity with ML frameworks such as PyTorch and TensorFlow, and specialized 3D/geometric processing libraries (e.g., PyTorch3D, Open3D, Trimesh, or similar). - Exceptional problem-solving skills with a focus on building algorithmic solutions from scratch. - Knowledge of cloud-based solutions and tools (AWS, GCP, or Azure) for scalable model training and distributed computing. (Note: The additional details of the company were not present in the provided job description.) Role Overview: As a Deep Learning Engineer specialized in 3D Computer Vision and Reinforcement Learning, you will be responsible for developing, implementing, and optimizing state-of-the-art models that address complex challenges in spatial AI and geometric processing. You will play a key role in a multidisciplinary team dedicated to pushing the boundaries of 3D representation, algorithmic generation, and autonomous agents, ultimately contributing to the research, development, and deployment of large-scale AI systems capable of interpreting, manipulating, and generating intricate 3D structures. Key Responsibilities: - Develop, implement, and optimize advanced deep learning models focusing on Computer Vision, 3D CNNs, and Geometric Deep Learning. - Design custom neural network architectures and autonomous agents for interacting with, interpreting, and generating complex 3D geometries, including CAD data and 3D meshes. - Lead and contribute to research initiatives centered around advanced deep learning models, particularly 3D Convolutional Neural Networks (CNNs), Geometric Deep Learning, and Deep Reinforcement Learning (DRL) for spatial problem-solving. - Conduct training and fine-tuning of complex models (e.g., DRL agents, 3D CNNs) in simulated and geometric environments using modern machine learning frameworks such as PyTorch and TensorFlow. - Work on scaling, optimizing, and enhancing the efficiency of custom algorithms and large models, including distributed training, parallelism, and hardware acceleration (GPUs, TPUs). - Collaborate with engineering teams to integrate 3D deep learning models and agentic workflows into robust, scalable production systems. Qualifications Required: - 1 to 4 years of relevant experience in developing deep learning models. - Degree in Computer Science, Applied Mathematics, Artificial Intelligence, or a related discipline. - Specialized coursework or research in 3D deep learning, reinforcement learning, and advanced algorithmic design. - Strong mathematical foundation. - Expertise in deep learning and machine learning algorithms, particularly in the context of 3D vision, reinforcement learning, and generative geometric models. - Proficiency in programming languages like Python and C++. - F