Hiring: MTS - AI Physics & Simulations Company: Collinear AI Location: San Francisco, CA Job Posted Time: 2026-09-15 13:04:11 Target Skills & Keywords : CI/CD, Deep Learning, LLM, Linux, Machine Learning, Project Management, Python, RAG, Unit Testing About the job Required Skills: •Execute Simulation Campaigns: Design and orchestrate large-scale simulation campaigns using domain-specific solvers (e.g., OpenFOAM, ANSYS, COMSOL, Abaqus). •Train & Validate Models: Train AI models on physics datasets and conduct rigorous evaluations of coverage, accuracy, and output quality against industrial validation standards. •Build Infrastructure & Tooling: Develop robust automated frameworks for dataset creation, simulation pipeline orchestration, and continuous model evaluation. •Integrate LLMs & Workflows: Architect agentic workflows and Retrieval-Augmented Generation (RAG) systems that seamlessly connect LLMs with engineering simulation pipelines. •Research Collaboration: Partner closely with the research team to analyze training runs, diagnose failure modes, and address data sparsity or architecture bottlenecks. •Technical Project Management: Lead research initiatives and manage technical communications with external engineering teams. Qualifications: •Technical Mastery: Solid grounding in deep learning principles paired with a strong foundation in physics or engineering sciences. •Framework Proficiency: Hands-on experience implementing and training deep learning models. •Software Engineering: Demonstrated ability to write clean, maintainable Python in Linux and High-Performance Computing (HPC) environments. •Communication: Outstanding verbal and written communication skills, with the ability to explain complex technical concepts to both specialized engineers and non-technical stakeholders. •Ownership & Mindset: Self-directed operator who thrives with autonomy, maintains a low-ego approach to collaboration, and excels in fast-paced environments at the intersection of simulation and ML. •Hands-on industrial or academic experience with simulation solvers (e.g., OpenFOAM, ANSYS, COMSOL, Abaqus). •Direct experience applying machine learning to physics simulations or surrogate modeling (e.g., Neural Operators, Physics-Informed Neural Networks). •Track record of automating large-scale simulation workloads on HPC clusters. •Meaningful contributions to large-scale open-source projects or production codebases. •Published research in top-tier machine learning (NeurIPS, ICLR, ICML) or computational engineering conferences/journals. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!