> Markdown version of [/jobs/ext/3647342-lead-machine-learning-engineer-medical-imaging-holo-x-holobeam-technologies-bethpage-ny](https://www.wearedevelopers.com/jobs/ext/3647342-lead-machine-learning-engineer-medical-imaging-holo-x-holobeam-technologies-bethpage-ny). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Machine Learning Engineer, Medical Imaging - Holo-X | Holobeam Technologies | Bethpage, NY - **Company:** Holobeam Technologies - **Location:** Old Bethpage, NY, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Dicom, Machine Learning, Pytorch - **Published:** October 9, 2026 - **Apply:** https://www.disabledperson.com/jobs/75949533-lead-machine-learning-engineer-medical-imaging-holo-x-holobeam-technologies-bethpage-ny ## About the Role * 6+ years of applied ML experience, or equivalent depth * Experience leading or mentoring engineers * Hands-on expertise in generative models and strong PyTorch skills * Medical imaging experience: multiple modalities, DICOM pipelines * Experience developing ML under design controls (IEC 62304, ISO 13485); 510(k) submission exposure a strong plus ## Description Lead Machine Learning Engineer, Medical Imaging - Holo-X | Holobeam Technologies | Bethpage, NY Holobeam Technologies is a medical imaging startup based in Bethpage, New York. We are building novel image reconstruction technology for clinical use. You will lead a team of two ML engineers, with the team expected to grow, and work directly with founder Gene Dolgoff, a pioneer in holography, on technical direction. What you'll do * Advance and refine our research pipeline, take it to a production-ready system, prepare it for regulatory submission, and see it through approval and into clinical use * Lead and grow a team of ML engineers * Build and validate models using various approaches including diffusion models and GANs * Work with DICOM pipelines and clinical imaging data