• Als AI Engineer (m/w/d) hast du die Chance, an wegweisenden Projekten zu arbeiten und intelligente Systeme zu entwickeln, die die Art und Weise, wie wir arbeiten und leben, revolutionieren. • Nutze deine Expertise im Machine Learning, um den Fortschritt in unserer Branche aktiv voranzutreiben und werde Teil von RLVNT!

• Create engaging social media content (LinkedIn, YouTube, Instagram, TikTok, Twitter) • Produce videos: tutorials, demos, behind-the-scenes • Showcase AI tools, design workflows, and marketing automation • Build an engaged audience in the AI/tech/marketing space • Collaborate with our team on content strategy • Stay on top of trends and incorporate them into content

About Us: Artera is an artificial intelligence company dedicated to transforming cancer care. We’ve developed foundation models that analyze clinical and pathology data, generating actionable insights that guide therapy selection and improve outcomes for cancer patients. By continuously improving these models, we aim to uncover the biological mechanisms driving cancer progression. We’re looking for experienced machine learning engineers to work on both product development and core algorithmic research. As a part of the 3rd generation of our core foundation model, you’ll contribute to efforts to identify new approaches to model training that amplify clinically relevant biology while remaining robust across datasets, institutions, and patient populations. You will help design, build, deploy, and continuously improve multimodal models—combining whole-slide images with clinical and molecular data—to predict molecular traits and patient outcomes. 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. Here are few posts from our teammates, partners and customer voices to highlight the work we do: - Artera Shapes the Future of Cancer Treatment Using Machine Learning on AWS - How Artera AI test allowed Bruno to avoid hormone therapy - Startups are using AI to predict responses to Cancer Drugs - ArteraAI validates its Prognostic Model in Advanced Prostate Cancer - How Artera Enhances Prostate Cancer Diagnostics Using AWS $140,000 - $180,000 a year In addition to base salary, equity is a core component of our compensation. We also offer 401k matching, unlimited paid time off (PTO), and more. The base salary is competitive and commensurate with experience, qualifications, and other factors to be discussed during the interview process. Equal Employee Opportunity:At Artera, we value bringing together individuals from diverse backgrounds to develop new andinnovative solutions for patients and physicians. As an equal opportunity employer, we do notdiscriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy),physical or mental disability, medical condition, genetic information gender identity orexpression, sexual orientation, marital status, protected veteran status, or any other legallyprotected characteristic.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: - Design rigorous physics problems reflecting professional practice; - Evaluate AI solutions for correctness, assumptions, and constraints; - Validate calculations or simulations using Python (NumPy, Pandas, SciPy); - Improve AI reasoning to align with industry-standard logic; - Apply structured scoring criteria to multi-step problems. What we look for This opportunity is a good fit for physicists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Physics or related fields, e.g. Engineering Physics, Thermodynamics, Statistical Mechanics, Optics and Acoustics, etc. - 3+ years of professional physics experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., CPhys, EurPhys, MInstP) and experience in international or applied projects are an advantage. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $55 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.