Quantivly’s mission is to increase access to medical imaging and enhance imaging care. Spun out of Boston Children’s Hospital, we are building the “air traffic control” system for medical imaging providers, using computers for what they do best (solving complex orchestration problems) so clinicians and staff can focus on what matters most: patient care.

Quantivly has built the first-of-its-kind unified data layer that unlocks imaging operational data previously trapped within hospital systems. Our initial application gives imaging providers unprecedented visibility into their operations. We have built a novel foundation model of operations and are now rapidly expanding to create the automation layer that will redefine how radiology departments operate. We are hiring a new AI Engineer to accelerate this vision and turn cutting-edge operational data into real-world impact for radiology teams.

Role Overview:

As an AI engineer at Quantivly, you will be a core member of the AI team and help build the intelligent systems that power our automation layer and knowledge-graph-driven insights. You will create end-to-end AI solutions that fuse diverse data signals to power actionable agents.

Your day-to-day responsibilities will include (but are not limited to):

Building reliable data pipelines and training workflows.
Designing, implementing, testing, and deploying AI models and agents aligned with the product roadmap.
Integrating models and agents to our platform services to support real workflow automation.
Bridging the gap between prototype and production by working cross-functionally to ship AI-powered features.
Ensuring model quality through evaluation frameworks, testing, and reproducibility.
Improving CI/CD for ML, model deployment systems, monitoring, cloud-based training, and scalable inference.
Expanding and optimizing our AI repositories and model library to accelerate the creation and deployment of new models and agents.
Staying current with applied ML and bringing practical advancements into our stack.

We are transforming radiology by injecting AI into imaging operations.

If you want to build real-world AI end-to-end –from training to deployment to impact– join Quantivly!

Compensation: Salary: $160k-180k, Equity: 0-0.25%

Responsibilities

Develop and maintain end-to-end machine learning pipelines, from data ingestion to production integration, supporting core components of our automation layer.
Implement clean, scalable Python code and reusable ML components that integrate seamlessly with our platform and MLOps tooling.
Prepare, process, and validate diverse data sources (HL7, DICOM metadata, operational logs, radiology report text) to ensure high-quality model inputs and consistent labeling.
Design evaluation frameworks, run experiments, and clearly communicate results, tradeoffs, and model behavior to both technical and non-technical stakeholders.
Stay updated with the latest advancements in machine learning and artificial intelligence, integrating relevant insights into ongoing projects.
Contribute to internal documentation, best practices, and shared AI standards to support a growing AI team and an expanding automation ecosystem.

Minimum Qualifications

3+ years of professional ML engineering experience, with demonstrated end-to-end ownership of model-driven features.
Strong applied ML skills: model development, feature engineering, evaluation, and productionization.
Experience with modern LLMs, embeddings, or retrieval-based methods (even if not in production).
Solid Python engineering competency (beyond notebooks): testing, structure, reliability.
Experience with core ML tooling (e.g., PyTorch or TensorFlow, Hugging Face, scikit-learn).
Strong problem-solving, debugging, and analytical skills.
Excellent communication and ability to collaborate in a fast-paced environment.
High ownership mindset and comfort working in an early-stage team where responsibilities evolve.
Bachelor’s degree or greater in Computer Science (preferred), Information Technology, or equivalent work experience.

Bonus Qualifications

Experience with Docker, or cloud services for ML deployment.
Experience with Reinforcement Learning.
Experience building evaluation frameworks or agents for quality checking.
Knowledge of DICOM, HL7, or medical imaging workflows.
Experience with ontology-driven or knowledge-graph-enhanced ML systems.
Background in radiology, healthcare, or regulated environments.
Published work(s) in recognized machine learning/artificial intelligence journals.

Who you are

You take pride in building simple, clean, elegant solutions to complex problems.
You are highly motivated and passionate about creating impactful software products.
You value technical excellence but know when pragmatism is necessary to meet deadlines.
You are curious and love diving deep into new technologies and understanding how things work.
You communicate clearly and effectively with cross-functional teams.
You thrive when given ownership and deliver high-quality results with minimal guidance.
You care deeply about reliability, performance, and engineering craftsmanship.

Working locations & additional information

Location: Based in our Somerville, MA office. We strongly favor hybrid candidates able to be in person at least 2 days per week, but will consider exceptional remote candidates.
Employment Status: Full-Time Employee with benefits (Medical, Dental, Vision, 401k with matching)
Sponsorship: Quantivly does not sponsor visas at this point : you must be authorized to work in the United States.

Our tech stack

Model Development: Python, PyTorch, PyTorch Geometric (PyG), Transformers
Serving & APIs: FastAPI, FastMCP, TorchScript

Equal Opportunity/Affirmative Action Statement. At Quantivly we celebrate difference. We are committed to ensuring an environment of mutual respect for every employee and proud to be an equal employment opportunity employer who does not discriminate against any person because of race, color, creed, religion, gender, gender identity, gender expression, national origin, citizenship, age, sex, sexual orientation, pregnancy, marital status, ancestry, physical or mental disability, military or veteran status, or any other characteristic protected by law. We believe a diverse and inclusive workplace is central to our success and actively seek to recruit, develop and retain the most talented people from a diverse pool of candidates.

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