Posted: 4 May
The role
We are seeking a highly skilled Senior Full Stack Software Engineer to join our team supporting research and foundation model development. This role operates at the intersection of research scientists, ML engineers, and infrastructure teams, enabling rapid experimentation, prototyping, and model deployment.You are comfortable working in a high-ambiguity environment where requirements are often not fully defined. Understanding problems, gathering context (including through modern AI tools), and iterating quickly are key aspects of the role. You will contribute across the stack, building systems that support model development, evaluation, and integration into production workflows. **Responsibilities**Work with 3D data (meshes/BREPs) and support 3D geometry processing and rendering systems Operate effectively in situations with evolving or unclear requirements **Minimum Qualifications** Strong programming skills in Python (or similar) Experience developing full stack applications (backend + frontend) Experience using modern AI/GenAI tools as part of the development workflow Familiarity with cloud infrastructure (e.g., AWS), Linux environments, and containerization (Docker) Experience with CI/CD tools and workflows Experience building or working with data pipelines Ability to work in fast-paced, ambiguous environments and drive tasks to clarity Bachelor's degree in computer science, Engineering, or equivalent experienceStrong problem-solving, communication, and collaboration skills **Additional Qualifications** Experience building prototypes in research or experimental settings Familiarity with workflow/pipeline orchestration tools (e.g., Metaflow) Experience working with 3D data, CAD systems, or rendering techniques Experience with frontend technologies (e.g., JavaScript, React) Ability to work across multiple domains (systems, data, UI) as needed **Preferred Skills**Experience supporting or deploying experimental ML models (evaluation, iteration, or internal use) Strong experience with Ray (data, training, or serving use cases) Familiarity with DevOps practices and tools (e.g., Kubernetes, Terraform) Proficiency in a low-level programming language (e.g., C, C++, Rust)Experience with other cloud platforms (Azure, GCP)
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