We are looking for a talented professional at Bunkerhill to help researchers bring their algorithms to the clinic through our new initiative: building a foundation model for medical imaging. Currently, researchers often start from scratch or utilize models pretrained on ImageNet, which requires substantial amounts of data to train algorithms. Our goal is to create a foundation model that allows researchers to fine-tune it and build clinically useful algorithms more efficiently. This initiative aims to enable researchers to develop robust, generalizable algorithms with reduced data requirements and leverage the Bunkerhill Consortium for validation, regulatory clearance, and clinical distribution.
Responsibilities include:
- Design, develop, and deploy machine learning algorithms and models focusing on Deep Learning and Computer Vision techniques.
- Define and operate batch processing pipelines.
- Create and maintain user documentation to assist researchers in onboarding their AI models.
- Develop large deep learning models with self-supervised learning on multimodal data.
- Communicate findings effectively to engineers, operators, and leadership.
- Collaborate with cross-functional teams to translate project requirements into technical solutions.
- Conduct research to stay updated with advancements in machine learning, deep learning, and computer vision.
- Optimize algorithms for performance, scalability, and efficiency considering real-world deployment constraints.
- Evaluate and validate models using appropriate metrics and datasets to ensure robustness and reliability.
- Mentor junior team members and contribute to knowledge sharing within the organization.
Requirements:
- Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or a related field.
- 3+ years of professional experience in a fast-paced, high-growth environment.
- Experience in developing machine learning solutions, particularly in Deep Learning and Computer Vision.
- Proficient in Python, PyTorch, TensorFlow, or similar frameworks for machine learning.
- Experience in training deep learning models with supervised learning.
- Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and infrastructure-as-code tools (e.g., Terraform, CloudFormation, Pulumi).
- CI/CD tooling experience (e.g., GitHub Actions, GitLab CI, CircleCI, Jenkins) is a plus.
Benefits:
- Competitive target annual salary range: $140,000—$240,000 USD, depending on work location.
- Full-time offers also include equity and benefits (medical, dental, vision, commuter, and 401(k)).
- Hybrid work schedule (3 days in office).
- Professional development opportunities.
- Dynamic and inclusive work culture with a focus on innovation and collaboration.
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