Staff Software Engineer, Machine Learning

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.

**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

$230-270k base salary

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