Averywell
Artificial Intelligence Engineer
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Company Description
Averywell is dedicated to advancing early cancer detection through the application of cutting-edge artificial intelligence and data-driven technologies. The company focuses on developing tools and systems that help healthcare professionals identify cancer at earlier, more treatable stages. Team members collaborate closely with medical experts and researchers to translate complex clinical challenges into practical AI solutions. Averywell offers opportunities to work on impactful projects, contribute to life-saving innovations, and grow in a mission-driven environment.
Role Description
In this role, the engineer will design, build, and optimize AI models that support early cancer detection, including tasks such as data preprocessing, model training, evaluation, and deployment. Day-to-day responsibilities include:
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- Collaborating with cross-functional teams
- Implementing algorithms for pattern recognition and natural language processing
- Integrating neural network models into production-ready software systems
- Contributing to software development best practices
- Monitoring model performance
- Addressing technical issues
- Documenting solutions to ensure reliability, scalability, and compliance with healthcare standards
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Qualifications
- Strong foundation in Computer Science and Software Development, including data structures, algorithms, and production-grade coding.
- Experience with Pattern Recognition and Neural Networks, with a focus on building and optimizing machine learning and deep learning models.
- Knowledge of Natural Language Processing (NLP) techniques and tools for processing clinical or scientific text data.
- Proficiency in programming languages commonly used in AI (such as Python) and frameworks (such as TensorFlow, PyTorch, or similar).
- Experience working with large datasets, data pipelines, and version control tools (e.g., Git).
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Engineering, or a related field, or equivalent practical experience.
- Ability to collaborate effectively in an on-site, multidisciplinary team and communicate technical concepts clearly to non-technical stakeholders.
- Background in healthcare, medical imaging, or biotechnology is beneficial but not required.
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