R&D Engineer II ( Machine Leaning )

Key Skills

C++, CUDA kernels, Data Analysis, Deep Learning, JAX framework, Machine learning techniques, OpenCL, Python Programming, PyTorch, Scikit-learn, TensorFlow

Job Description

Summary / Role Purpose

The R&D Engineer II contributes to the research and development of software products and supporting systems. As part of Office of CTO, in this role you will do machine learning and deep learning with diffusion models and concepts from LLMs to research and build proof concepts and work with larger product organization for integration into products.

Key Duties and Responsibilities

• Organic research on diffusion models and other scientific ML models for learning physics with a goal towards building foundation models for 3D geometry and physics
• Incubate research with deep learning tech from Ansys with goal to apply them for numerical simulation in context of fluids, structures, electromagnetics, optics, and electronics.
• Participates in brainstorming, planning, architecture and research.
• Collaborate with product engineering teams to drive real-time model implementations and new feature creations.
• Maintains efficient/scalable processes for large scale data analyses, model development, framework development, model validation and model implementation.
• Diagnose and fix code problems.
• Create unit regression and/or system-level tests to thoroughly validate new features or changes.
• Works under the general supervision of a development manager

Minimum Education/Certification Requirements and Experience

• BS in Engineering, Computer Science, or related field.
• Working experience developing machine learning code in C++ or Python with a focus on deep learning frameworks like TensorFlow, PyTorch, JAX, or Scikit Learn  

Preferred Qualifications and Skills

• Masters or a PhD degree with 1 yrs experience in generative models such as GANs or Stable diffusion. 
• Experience with GPU programming (CUDA, OpenGL, OpenCL, DirectX) and scientific ML and applied ML for physics 
• Publication in leading journals or conferences such as CVPR, NeurlPS, ICML or ICLR
• Experience with 3D geometry, computer graphics or computer vision