Machine Learning Engineer, PathAI
ML Core
More information about location
AI-powered pathology tools
Open for applications
AI-powered pathology tools
201-500 employees
Open for applications
More information about location
201-500 employees
Company mission
To improve patient outcomes with AI-powered pathology.
Role
Who you are
- We’re seeking a Machine Learning Engineer with experience in ML Ops and tooling who also has a strong understanding of applied machine learning
- Bachelor’s or Master’s degree plus 3-5 years of professional experience with a focus on artificial intelligence and machine learning
- Proven track record in developing, deploying, and maintaining state-of-the-art ML models in scalable production environments
- Strong experience in building and managing large-scale ML pipelines, feature and embedding stores, model monitoring, and performance evaluation systems
- Hands-on proficiency with MLOps technologies such as Kubernetes, AWS, Docker, Terraform, Helm, Kafka, Airflow, Kubeflow, Argo, Ray, and GitLab/GitHub Actions for end-to-end ML lifecycle management
- Excellent proficiency in Deep Learning frameworks (Pytorch/Tensorflow), Python (including Scipy, Numpy, Pandas) and software engineering skills. Strong analytical and quantitative skills
- Knowledge of recent advances in machine learning and computer vision concepts, including but not limited to transformer-based models, self-supervised learning, advanced segmentation models, inference-optimization techniques
- Strong communication skills and the ability to collaborate effectively in a cross-functional environment
- Intellectual curiosity and the ability to learn quickly in a complex space
- Publications or research in fields related to machine learning and biomedical science are a bonus
- Proficiency in using AI Assistants for code development (Cursor, CoPilot) is a bonus
What the job involves
- You’ll work at the intersection of ML engineering and operations, building robust tools, systems, and platforms that empower our foundational models and accelerate the end-to-end ML lifecycle
- Design, build, and optimize ML infrastructure and platforms supporting foundational base models, enabling rapid iteration from training to deployment
- Develop robust and scalable tooling to streamline end-to-end ML workflows including data ingestion, dataset creation & management, automated training, comprehensive evaluation, and seamless model deployment
- Collaborate closely with ML engineers, researchers, software engineers, and product managers to effectively integrate and deploy innovative ML methods and base models into production systems
- Implement and optimize automated ML operations through advanced CI/CD pipelines, leveraging technologies like Kubernetes, Docker, Helm, and Airflow for orchestration and infrastructure-as-code
- Standardize and enhance model performance, reliability, data efficiency, and inference latency across diverse ML use-cases, utilizing rigorous benchmarking and iterative improvement methodologies
- Engage in technical research and prototyping to evaluate new tools, frameworks, and methodologies that enhance MLOps and applied ML capabilities
- Champion best practices, contribute to documentation, mentor team members, and participate actively in knowledge sharing and continuous improvement initiatives
- 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
Our take
PathAI is a leader in the field of AI-powered pathology, dedicated to transforming patient outcomes by harnessing the power of AI. Its core mission revolves around enhancing the accuracy of diagnoses and the effectiveness of disease treatments, particularly in critical areas like cancer.
PathAI's pioneering spirit is evident through its breakthroughs, exemplified by innovations such as the AIM-HER2 Breast Cancer algorithm. This tool automates HER2 scoring and introduces a novel approach with additive multiple instance learning (aMIL) heatmaps, offering insights into scoring mechanisms. Additionally, PathAI's PathExplore panel of human interpretable features (HIFs) fosters collaborative research, thus enhancing understanding of the tumor microenvironment.
As the company moves forward, it is poised to continue shaping the landscape of AI-powered pathology, driving advancements in medical research, diagnostics, and drug development, while upholding its central mission to improve patient well-being.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 7 rounds)
May 2021
$165m
SERIES C
Nov 2019
$15m
SERIES B
Total funding: $258.6m
Company benefits
- Comprehensive Health Plans
- Paid Time Off & Paid Holidays
- Wellness Benefits
- 401(k) Program
- Parental Leave
Company HQ
West Fens, Boston, MA
Leadership
Andrew Beck
(CEO)Graduated from Stanford University with a PhD in Biomedical Informatics. Previously worked at Harvard Medical School as a Professor of Pathology.
Aditya Khosla
(Advisor)Graduated from the Massachusetts Institute of Technology with a PhD in Computer Science. They now serve as the CTO at Iterative Health.
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