Senior ML Engineer
Description For Senior ML Engineer
Qventus is seeking a Senior Machine Learning Engineer to join their healthcare operations platform team. The role focuses on building and scaling AI-powered healthcare solutions, with a strong emphasis on ML Ops. The position involves working across the complete ML lifecycle, from experimentation to deployment and monitoring. The company's mission is to simplify healthcare operations, enabling hospitals and caregivers to deliver better patient care. They've been recognized by the 2019 Black Book Awards and CB Insights as a top AI company.
The role requires expertise in developing and maintaining production ML systems, with particular focus on MLOps infrastructure. You'll work closely with data scientists, engineers, and stakeholders to design and deploy infrastructure for production ML and LLM models. The position offers competitive compensation ($170,000-$200,000) and comprehensive benefits including equity, paid time off, and various stipends.
Qventus works with leading hospitals across the United States, making real impact in healthcare operations. Their platform uses AI and ML to help healthcare staff make better operational decisions proactively. The company has demonstrated success in helping health systems during the COVID pandemic, winning the Robert Wood Johnson Foundation Emergency Response Challenge.
The ideal candidate will have 3+ years of ML systems experience, strong Python and SQL skills, and familiarity with LLM frameworks. They should be passionate about improving healthcare quality and patient outcomes through technology. The role offers an opportunity to work on meaningful problems while building scalable, reliable AI systems that directly impact healthcare delivery.
Responsibilities For Senior ML Engineer
- 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
Requirements For Senior ML Engineer
- 3+ years of experience developing and maintaining machine learning systems in production environments (Python, SQL)
- 1+ years experience supporting ML Ops infrastructure
- Hands-on experience with model lifecycle tools such as MLflow, SageMaker, or similar
- Familiarity with operationalizing LLMs or retrieval-augmented generation (RAG) systems
- Strong understanding of software engineering principles and writing maintainable, modular code
- Practical experience with AWS services, Databricks, Spark, Terraform
- Strong collaboration and communication skills
Benefits For Senior ML Engineer
- Open Paid Time Off
- Paid parental leave
- Professional development stipend
- Wellness stipend
- Technology stipend
- Employee referral bonus
- Employee stock option awards
