A Pioneering Force in AI Innovation
At Theta, we're not just developing AI; we're redefining it. Coming from the world of machine olfaction for diagnostics, our mission is to make sophisticated AI explainable and accessible, transforming how we interact with and understand artificial intelligence where it matters most. Our core product, Alchemy, embodies our commitment to multimodality, explainability, and no-code machine learning, setting new standards to make AI trustworthy in high-stakes scenarios. We have proven ourselves in lung cancer screening and are now ready to bring our advanced technology to a variety of applications.
The Opportunity
As part of Theta's dedicated team, you'll be contributing to 'Alchemy,' our core product that is setting the benchmark for machine olfaction and explainable AI. You will play a pivotal role in advancing our AI capabilities, focusing on generative and explainable AI techniques to empower healthcare professionals with actionable insights. In the near future, we plan to expand way beyond the world of medicine.
What We Seek
- A passion for AI and a belief in its potential to drive positive change, particularly in key impact areas like healthcare.
- Eagerness to tackle complex problems, develop innovative solutions, and contribute to a team that values creativity and forward-thinking.
- Commitment to our mission of making AI more transparent and understandable, ensuring that our advancements remain aligned with human needs and ethical standards.
Key Responsibilities
- Design and develop generative machine learning models and systems, focusing on healthcare applications.
- Implement cutting-edge generative models like GANs, VAEs, and large language models to synthesize and interpret multimodal sensor data.
- Develop simulations leveraging generative models to synthesize multimodal sensor data.
- Create and engineer a robust framework for explainable AI, enabling medical professionals and physicians to receive in-depth and detailed responses about AI decision-making processes.
- Develop and engineer intuitive data visualization tools to enhance AI explainability.
- Utilize and engineer solutions using few-shot learning and prompt-based techniques to swiftly and rapidly adapt models to new healthcare scenarios and tasks.
- Enhance and optimize generative model performance for deployment on various platforms, ensuring scalability, efficiency, and efficient deployment on embedded systems.
- Establish and engineer comprehensive testing protocols and frameworks to ensure model reliability, robustness, safety, and performance in clinical settings.
- Collaborate with cross-functional teams to identify and assess use cases for generative AI in novel healthcare applications.
- Stay abreast of the latest advancements in AI/ML, continuously integrating new techniques to improve our solutions.
- Develop and deploy generative AI models for image generation, text generation, and other healthcare applications.
- Develop new methods for training AI models on both small and large datasets.
Requirements
- At least a Bachelor's or Master's degree in a relevant field (Computer Science, Machine Learning, Statistics, Mathematics, Physics, or related).
- At least 2 years of experience in AI/ML research, with a focus on explainability.
- 1+ years experience building and deploying AI systems.
- Proficiency with Python, TensorFlow, PyTorch, and related libraries.
- Demonstrated experience with large generative models and AI system deployment.
- Good software engineering skills and knowledge of model optimization techniques.
- Good knowledge of neural networks, transformers, and fundamental AI techniques.
- Strong understanding of neural networks, transformers, and core AI principles.
- Proven ability to tackle complex challenges using novel applications of AI.
- Excellent teamwork and communication skills combined with the ability to work independently, with fluency in English (additional European languages are a plus).
- Passion for advancing the use of safe and explainable AI in healthcare.
- Existing working permit and current first residence in USA or EU.
Nice-to-Have
- The theoretical foundations of generative AI, including probability theory, statistics, and machine learning.
- The theoretical foundations of multimodal learning and data fusion, including embedding models, extended Kalman filtering, and other techniques.
- Research and/or engineering experience in explainable AI or data visualization.
- Cloud development experience with Google Cloud Platform and/or Amazon Web Services.
- Experience in application or research in the medical or healthcare industries.
Joining Theta means
- Pushing the boundaries of machine perception, contributing to a platform that interprets the world in a way no machine has done before.
- Diving into the intricacies of multimodal AI, working with a variety of data types to craft comprehensive and explainable insights.
- Engaging in the development of no-code ML solutions, empowering users with transparency and customization in their AI tools.
- Working on groundbreaking socially important applications, e.g. in healthcare, where your contributions could lead to early detection and better diagnostic tools, significantly affecting patient care and outcomes.
- Collaborating with a team of passionate experts dedicated to creating cutting-edge, user-centric AI solutions.
- Being part of a culture that values innovation, inclusivity, and professional growth.