About Us: Artera is an AI startup that develops medical artificial intelligence tests to personalize therapy for cancer patients. Artera is on a mission to personalize medical decisions for patients and physicians on a global scale.
As a Machine Learning Engineer at Artera, you will help develop AI-based biomarkers that support the personalization of cancer therapy. You will work on multimodal deep-learning models that integrate large-scale pathology whole-slide images with diverse modalities to predict patient risk and response to therapy. Training models on pathology images poses unique computational and modeling challenges, and you will contribute to developing robust, scalable solutions in this space. You will collaborate closely with fellow ML engineers, biostatisticians, scientific directors, and product partners to build, validate, and deploy models that ultimately impact patient care.
Essential Responsibilities:
Develop and evaluate AI-based biomarkers using multimodal data.
Design, implement, and improve machine-learning models to predict patient outcomes and treatment response.
Contribute to the end-to-end model development lifecycle, including data preparation, training, evaluation, and validation.
Support the productionalization, launch, and monitoring of machine-learning models in collaboration with platform and product teams.
Conduct research and experimentation to improve model performance, robustness, generalizability, and interpretability.
Collaborate with biostatistics, clinical, and product partners to translate clinical questions into machine-learning solutions.
Contribute to scientific publications and conference submissions alongside the broader research team.
Experience Requirements:
2+ years of industry experience using PyTorch or TensorFlow.
Experience contributing to machine-learning systems deployed or maintained in production environments.
Ability to clearly communicate complex technical concepts to cross-functional, non-ML collaborators.
Desired:
Experience working with large-scale image data or computer vision models.
Familiarity with self-supervised representation learning (e.g., MoCo, DINOv2) and / or vision–language models (VLMs) and multimodal representation learning.
Interest in healthcare, medical imaging, or applied machine learning in regulated or high-impact domains.
Equal Employee Opportunity: At Artera, we value bringing together individuals from diverse backgrounds to develop new and innovative solutions for patients and physicians. As an equal opportunity employer, we do not discriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information gender identity or expression, sexual orientation, marital status, protected veteran status, or any other legally protected characteristic.
