Zus Health
Machine Learning Engineer, Data Acquisition
Machine Learning Engineer
Remote
$150,000 - $190,000 a year
2025-07-19
Job descriptions
About Zus Health: Zus is a shared health data platform devoted to accelerating healthcare data interoperability, providing easy-to-use patient data via API, embedded components, and direct EHR integrations.
Role Overview: As a Machine Learning Engineer on the Data Acquisition (DA) Team, you will leverage your ML expertise to improve the collection and processing of health data. The DA team is responsible for building and running microservices infrastructure that connects with external health data networks, collects large-scale patient information, loads data into Zus data stores, and supports service requests by customers and internal stakeholders.
Main Responsibilities:
- Use experience with large language models (LLMs) and MLOps to develop, deploy, and optimize ML solutions.
- Collaborate with DA software engineering to design and scale ML solutions for key business challenges.
- Conduct research to explore and implement new ML methodologies and techniques.
- Develop prototypes and feedback mechanisms for constant model improvement.
- Create CI/CD pipelines and automate workflows for scalable, reliable ML operations.
- Present learnings and coach the team in the application of ML techniques.
- Product innovation: Discover opportunities for better, cost-effective data collection, scaling, and normalization.
- Continuous growth: Stay current on ML and AI advancements.
- Build robust data pipelines in collaboration with engineers to ensure data quality for model training and evaluation.
- Implement and manage MLOps practices for deployment and monitoring.
- Collaborate closely with software engineers, product managers, and stakeholders.
Requirements
Must-Have:
- 3+ years of experience in machine learning, focusing on model development and MLOps, with proven work using LLMs.
- Proficiency in Python, Java, or Go.
- Strong understanding of ML frameworks/libraries (TensorFlow, PyTorch, Scikit-learn).
- Experience with MLOps tools and platforms.
- Familiarity with cloud services (AWS, GCP, Azure) & distributed computing.
- Excellent analytical and problem-solving skills, with attention to detail.
- Strong verbal and written communication; able to explain complex technical topics to non-technical stakeholders.
- Proven ability to work effectively in collaborative team environments.
Bonus:
- Knowledge of natural language processing (NLP) techniques and libraries.
- Healthcare industry experience.
- Experience designing and developing software for distributed data pipelines.
- Bachelor’s degree in Computer Science or Statistical Science preferred; advanced degrees are a plus.
Benefits
Compensation & Benefits:
- Competitive salary ($150,000 - $190,000) plus equity.
- Robust health insurance and wellness benefits.
- 401k plan with matching.
- Unlimited PTO (paid time off).
- Opportunity to work in a mission-driven, passionate team environment with a focus on innovation and positive change in healthcare.
