Machine Learning Engineer

About Nucs AI

Nucs AI is revolutionizing cancer care through cutting-edge AI and medical imaging technology. Founded in 2024 by a multidisciplinary team of oncologists, AI researchers, and healthcare innovators, we’re tackling one of medicine’s most pressing challenges: the growing demand for accurate, timely cancer diagnostics in the face of rising scan volumes and limited radiologist capacity.

We sit at the intersection of diagnostics and treatment planning—building AI-powered tools at the convergence of medical imaging, radioligand therapy, and artificial intelligence. Starting with prostate cancer and expanding across oncology, we partner with world-leading medical institutions and pharmaceutical companies across the US, Europe, and Australia to bring precision oncology into everyday clinical practice.

Our mission is to enhance diagnostic precision and expand access to expert-level cancer care, improving patient outcomes worldwide. We’re venture-backed, early-stage, and building a team that blends deep clinical expertise with engineering intensity—moving with the rigor the medical field demands and the speed the problem deserves.

The Opportunity

As an ML Engineer at Nucs AI, you will be at the forefront of developing and deploying cutting-edge machine learning models to power our AI-driven medical software solutions. Your role will involve building algorithms that analyze medical images and data, driving innovation in prostate cancer diagnosis and treatment. You will work closely with our engineering teams to ensure that our AI models are scalable, secure, and aligned with clinical and regulatory standards.

What You'll Build

• Model Development: Design, train, and optimize machine learning models for medical image analysis, leveraging deep learning techniques (e.g., CNNs, Vision Transformers, Multi-Modal LLMs).

• Data Processing: Build data pipelines to clean, preprocess, and augment large datasets of medical images, ensuring the highest accuracy of AI models.

• Integration: Collaborate with back-end developers to integrate AI models into our software solutions for seamless deployment in clinical environments.

• Cloud-Based AI: Develop scalable AI solutions on cloud platforms (Google Cloud preferred) using tools such as PyTorch, ONNX Runtime or similar.

• Regulatory Compliance: Ensure AI models and data processing adhere to healthcare regulations like HIPAA and meet medical industry standards.

• Evaluation Pipeline: Build strong evaluation pipelines to extract insights about trained model performance.

What You Bring

• Strong proficiency in machine learning frameworks: PyTorch and ONNX

• Experience with medical imaging technologies and datasets: DICOM, NIFTY and similar

• Expertise in developing deep learning models for 3D image segmentation

• Strong expertise in fine-tuning and deployment of multi-modal LLMs

• Familiarity with cloud platforms (Google Cloud or AWS)

Bonus Points

• Experience in healthcare/medical software development

• Previous experience with PACS integration

Why Nucs AI

• Mission with real impact – Your work directly improves how cancer patients are diagnosed and treated.

• Ground-floor opportunity – Early-stage company, meaningful equity, and outsized influence on the direction we take.

• World-class collaborators – Work alongside leading oncologists, nuclear medicine physicians, and AI researchers globally.

• Massive market tailwinds – Radioligand therapy and AI-driven oncology are multi-billion dollar growth markets.

• Autonomy and flexibility – Remote-first, flexible working. We hire great people and trust them to deliver.

• Equity upside – Competitive equity package. We’re building something big and want you to share in it.

How to Apply

Submit your resume and a brief note on why this role and Nucs AI excite you.

Equal Opportunity

Nucs AI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all team members. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.