Description review

Machine Learning Engineer III (Applied Research & Model Development)

PathAI · United States · back to the listing

HR standards

61/100

needs work

Title ↔ description

88/100

strong

Reads as

Machine Learning Engineer

100% confident

What this role officially is

data scientist — ESCO, the EU occupation classification

Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.

Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist

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What the listing never says

  • No section describes what the person would actually do. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

PathAI's mission is to improve patient outcomes with AI-powered pathology. Our platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine learning and artificial intelligence. We have a track record of success in deploying AI algorithms for histopathology in translational research, pathology labs and clinical trials. Rigorous science and careful analysis is critical to the success of everything we do. Our team, composed of diverse employees with a wide range of backgrounds and experiences, is passionate about solving challenging problems and making a huge impact on patient outcomes.

The Opportunity

We are seeking Machine Learning Engineers (Applied Research & Model Development) to tackle unique machine learning challenges to advance medicine and improve patient care. You will work closely with teams across biomedical data science, product development, translational research, MLOps, and platform engineering to develop and deploy machine learning models for our AI products and services.

You will have the opportunity to work in a company where all employees put patients first. We believe that every team member provides valuable contributions to our success, and no task is too small for anyone if it's important to our company goals. Every PathAI employee is a contributor to our mission to pioneer better patient care by providing the best, most innovative AI tools to biotech, pathologists, clinicians and healthcare organizations. You will work alongside and with leading innovators in the field of AI and medicine and you will play a critical role in product development to impact patient outcomes.

• You will design, develop, and deploy machine learning models for research and product development projects.

• You will collaborate cross-functionally with scientists, engineers, and product teams to translate biological and clinical requirements into scalable ML solutions.

• You will contribute to experimental design and analysis, including ideation, documentation, and reporting.

• You will participate in knowledge sharing and team initiatives (e.g., design reviews, journal clubs, ML best practices, governance activities).

• You will improve ML pipelines and infrastructure in partnership with MLOps and platform teams.

• You will publish and present scientific work, supporting abstracts, manuscripts, and conference contributions.

Who You Are:

(Required)

• You have a Master’s degree in Machine Learning, Computer Science, Data Science, Statistics, Applied Mathematics (or a closely related discipline) with 5 or more years of experience; or a PhD Machine Learning, Computer Science, Data Science, Statistics, Applied Mathematics (or a closely related discipline) with 3 or more years of experience.

• You have a proven track record of developing and deploying machine learning models into production or research applications.

• You are highly proficient in Python, ML frameworks, and data pipeline development.

• You have demonstrated the ability to work independently, lead/contribute to experimental design, and improve ML workflows.

• You have demonstrated the ability to collaborate across scientific and engineering teams.

Preferred:

• You have strong interpersonal and communication skills, with the ability to explain technical concepts to non-experts and thrive in ambiguous environments.

• You have excellent organizational skills and the ability to prioritize and manage multiple projects efficiently.

This position is based in Boston, NYC or remote.
Relocation benefits are not available for this position.

The expected salary range for this position based on the primary location Boston, MA is $130,500 - $200,100. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law.

PathAI is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

Originally posted on Himalayas

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 12 points (from 73 before penalties). Reviewed 21 Sep 2026.