Machine Learning Engineer III (Applied Research & Model Development)
About this role
Translating complex biological and clinical requirements into scalable machine learning solutions remains a core challenge in deploying AI for digital pathology. PathAI addresses this need by developing algorithms that improve diagnostic accuracy and treatment efficacy for diseases such as cancer.
Joining the applied research and model development group means designing, building, and launching machine learning models alongside biomedical data science, product development, and MLOps teams. Members of this group also contribute to experimental design, refine infrastructure, and share scientific findings through publications and conferences.
Candidates who succeed here typically combine advanced academic training in a quantitative discipline with hands-on experience in production environments. Someone who thrives in collaborative, cross-functional settings and prioritizes patient outcomes will find a strong alignment with the company goals.
What you will do
- Design, develop, and deploy machine learning models for research and product development projects.
- Collaborate cross-functional teams including scientists, engineers, and product groups to turn clinical requirements into scalable solutions.
- Contribute directly to experimental design, ideation, documentation, and reporting.
- Take part in internal knowledge sharing initiatives, design reviews, journal clubs, and governance activities.
- Partner with MLOps and platform teams to enhance machine learning pipelines and infrastructure.
- Publish and present scientific work through abstracts, manuscripts, and conference contributions.
What you need
- Possess a Master’s degree in Machine Learning, Computer Science, Data Science, Statistics, Applied Mathematics, or a related field with at least 5 years of experience, or a PhD with 3 or more years of experience.
- Demonstrate a proven track record of developing and deploying machine learning models into production or research applications.
- Maintain high proficiency in Python, common machine learning frameworks, and data pipeline development.
- Show the ability to work independently while leading or contributing to experimental design and workflow improvements.
- Exhibit strong cross-functional collaboration skills across scientific and engineering teams.
Nice to have
- Strong interpersonal and communication skills with the ability to explain technical concepts to non-experts
- Ability to thrive in ambiguous environments and manage multiple projects efficiently
Skills and tech stack
Questions candidates ask
Where is this job located?
This position is based in Boston, New York City, or remote. Relocation benefits are not available for this position.
What is the salary range for the role?
The expected salary range based on the primary location in Boston, MA is $130,500 to $200,100. Actual pay is determined based on experience, qualifications, geographic location, and other job-related factors permitted by law.
Who will I be working with?
You will work closely with teams across biomedical data science, product development, translational research, MLOps, and platform engineering. You will also collaborate with scientists, engineers, and product teams.