Role Overview
You’ll join a growing Machine Learning team in a mission-driven startup that develops AI-powered medical software. As a senior contributor, you’ll take full ownership of defining, designing, and operating scalable deep learning and analytics pipelines. The primary focus will be on detecting and classifying conditions in medical imagery (specifically dental x-rays). This role sits at the intersection of cutting-edge ML, medical imaging, and software engineering—impacting real-world clinical outcomes and regulatory processes.
Key Responsibilities
- Architect and implement robust infrastructure for high-performance deep learning and analytics workflows
- Lead development of computer vision systems targeting diagnosis from x-ray images
- Manage large-scale datasets, define sampling strategies, and establish performance evaluation metrics
- Collaborate directly with researchers, clinicians, and regulatory bodies to shape product outcomes
- Work closely with leadership and advisors with academic affiliations to Harvard and MIT
- Own end-to-end projects, from model conception to deployment in a regulated clinical environment
Required Qualifications
- M.S. or Ph.D. in Computer Science, Machine Learning, or a related technical field
- At least 4 years of hands-on experience developing deep learning models and data pipelines
- Proficiency in at least one major ML framework (PyTorch, TensorFlow, or Keras)
- Production-grade software development skills in Python, including testing and version control
- Aptitude in understanding and implementing technical research literature
- Excellent communication, teamwork, and proactive/self-driven attitude
Nice-to-Have Skills
- Evidence of high-quality software development (e.g. public code contributions)
- Experience working with medical image datasets or domain-specific computer vision tasks
- Familiarity with statistical data analysis, performance measurement, and visualization
- Prior exposure to cloud-based platforms (e.g. AWS)
- Mentorship or leadership in technical teams
What You’ll Gain
- A fast-paced, collaborative environment offering steep learning and technical stretch
- Opportunity to mentor others and shape team culture in an agile, early-stage tech venture
- Work on medically impactful ML systems being adopted by clinicians nationwide
Interview Process
- Initial screening with recruiters.
- Two technical interviews (technical/behavioral interview and a coding exercise)
- Final evaluation and qualification with recruiters.