Role

We are looking for a Staff Machine Learning Engineer to help us build a best in class ML Ecosystem to advance our product suite with clinical AI. The ideal candidate works exceptionally well across disciplines and delivers high quality outcomes continuously, with a relentless focus on reliable systems and developer experience.

SmarterDx builds clinical AI that empowers hospitals to analyze the complete record of every patient to fully capture the value of care delivered. Founded by physicians in 2020, its proprietary AI platform understands the nuances of clinical reasoning, enabling hospitals to true the patient record for every discharge. By doing so, hospitals can recover millions in earned revenue, enhance care quality metrics, and optimize healthcare operations. Become a Smartian and help optimize the way the healthcare system works for everyone. Learn more at smarterdx.com/careers.

**This role is fully remote within the US**

What You’ll Do

• Craft, implement, and maintain MLOps tools and practices, including continuous integration, delivery, and monitoring of machine learning systems.
• Optimize model performance and scalability, ensuring high reliability and efficiency.
• Build tools to improve the lives of our data scientists.
• Contribute to the design and architecture of our ML systems.

What You Bring

• 10+ years of development experience with a focus on Machine Learning and MLOps roles

• Strong proficiency in Python and SQL, with experience in machine learning libraries (Pytorch, Tensorflow)

• Experience with deploying and managing ML models in production environments, including familiarity with Docker, Kubernetes, or similar technologies.

• Understanding of CI/CD best practices for machine learning, including automated testing and deployment pipelines.

• Experience with cloud platforms (preferably AWS) and their machine learning services.

• Experience project managing a small team using a modern agile methodology

• Experiencing influencing a cross-disciplinary organization to adopt best practices

• Familiarity with infrastructure as code (e.g., CDK, Terraform) and configuration management tools.

• Strong understanding of data engineering and architecture principles.

• Excellent collaboration and communication skills, with a passion for solving challenging problems in a team environment.

Nice To Haves

• You're a former startup founder, or have been the first engineering hire at a startup
• Experience in the health tech domain, particularly in hospital billing systems
• Experience with end-to-end machine learning project lifecycle, from data collection and model training to deployment and monitoring.
• Deployment of LLM systems into Production environments.
• Contributions to open-source projects or active participation in the machine learning community.

Our Tech Stack

• Python, PyTorch, pandas/Polars, Airflow, Snowflake, dbt, AWS, MLflow, Sagemaker, Terraform, K8s

Compensation

$220-270k base + equity incentives