Job description
Have you ever found yourself or a loved one waiting hours and hours in a hospital Emergency Room to get care? Or have you ever had a surgery scheduled for months in the future that needed to happen sooner? Unfortunately, our healthcare system is full of these types of operational problems. Our work saves lives and helps hospitals cut tens of millions of dollars in operational costs, while improving the quality of care they’re able to deliver.
Qventus is a real-time decision making platform for hospital operations. Our mission is to simplify how healthcare operates, so that hospitals and caregivers can focus on delivering the best possible care to patients. We use artificial intelligence and machine learning to create products that help nurses, doctors, and hospital staff anticipate issues and make operational decisions proactively.
Qventus works with leading public, academic and community hospitals across the United States. The company was recognized by the 2019 Black Book Awards in healthcare for patient flow and by CB Insights as a 2019 top 100 Most Promising Company in Artificial Intelligence. In 2020, Qventus won the Robert Wood Johnson Foundation Emergency Response for the Healthcare System Innovation Challenge through its work helping health systems across the country plan for and operate in the COVID pandemic.
Qventus is looking for a Senior Machine Learning Engineer with a strong ML Ops focus to build and scale our AI-powered healthcare solutions. This role is ideal for someone who enjoys working across the ML lifecycle — from experimentation and feature engineering to deployment, monitoring, and iteration — with a strong focus on productionization and platform reliability. Our Data Science team supports everything from ML-based operational predictions to LLM-based assistants and spans the full machine learning lifecycle — from training and evaluation, to model deployment, versioning, and monitoring.
As a Senior ML Engineer in the Data organization, you’ll work closely with data scientists, data engineers, and platform partners to design, deploy, and support the infrastructure behind our production ML and LLM models. You’ll lead efforts in packaging, monitoring, and scaling models across critical healthcare workflows, while also contributing to experimentation and development as needed. Your work will help ensure our AI systems are reliable, reproducible, and ready for real-world impact — enabling care teams to make better, faster decisions across the hospital. You will be strongly motivated to have an impact in the company and dedicated to helping improve the quality of healthcare and patient outcomes.
Key Responsibilities
Build and support end-to-end ML pipelines for training, validation, deployment, and monitoring of traditional ML and LLM-based solutions
Partner with data scientists to productionize models with a focus on reproducibility, observability, and runtime efficiency
Manage ML infrastructure, including experiment tracking, model versioning, and deployment tooling
Contribute to the design and implementation of scalable, low-latency model inference and batch prediction systems
Key Qualifications
3+ years of experience developing and maintaining machine learning systems in production environments (Python, SQL)
1+ years experience supporting ML Ops infrastructure (model packaging, orchestration, observability, CI/CD)
Hands-on experience with model lifecycle tools such as MLflow, SageMaker, or similar
Familiarity with operationalizing LLMs or retrieval-augmented generation (RAG) systems; Exposure to LLM frameworks and libraries (Langchain, LlamaIndex, HuggingFace, etc.)
Strong understanding of software engineering principles and writing maintainable, modular code
Practical experience with the following tools & services: AWS services (Lambda, S3, RDS, CloudWatch), Databricks, Spark, Terraform (Atmos)
Strong collaboration and communication skills — able to partner closely with product, clinical, and engineering stakeholders
Nice to Have
3+ years applied or research experience using a wide variety of statistical and machine learning techniques - particularly in NLP, explainable ML (Python)
Experience supporting cloud-based, highly available, observable, and scalable data platforms utilizing large, diverse data sets in production to meet ambiguous business needs
Strong background in data quality validation and model monitoring in healthcare or regulated environments
Ability to contribute to feature engineering or algorithm tuning in partnership with domain experts
Prior experience working in healthcare, particularly with EMR, claims, or hospital operations data
Master’s degree in Computer Science, Engineering, or related field, or equivalent industry experience
The salary range for this role is $170,000 to $200,000. Qventus salary bands represent market data across different geographies. We consider several factors when determining compensation, including location, skills and qualifications, and prior relevant experience. Salary is just one component of Qventus’ total package. Some of our key benefits and perks* include but are not limited to: Open Paid Time Off, paid parental leave, professional development, wellness, and technology stipends, generous employee referral bonus, and employee stock option awards.
We believe that diversity, equity, inclusion, and belonging are fundamental to improving healthcare and society, and that’s why we’re building a company that leads the way. We hold ourselves accountable to using fair hiring processes that mitigate the negative impacts of unconscious bias. We also work to ensure that people from underrepresented groups play meaningful roles on both sides of the interview table. We are an equal opportunity employer and give all qualified applicants consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.
Candidate information will be treated in accordance with our candidate privacy notice which can be found here: https://qventus.com/ccpa-privacy-notice/
Employment is contingent upon the satisfactory completion of our pre-employment background investigation and drug test.
*Benefits and perks are subject to plan documents and may change at the company’s discretion.
