Role

We are looking for a Senior 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

• Build and scale machine-learning driven features across multiple products
• Design reusable architecture that powers and accelerates machine learning development across the company
• Deploy and maintain machine learning models and pipelines in production environments.
• Work closely with data scientists, data engineers, and application engineers to integrate ML models into the broader SmarterDx platform.
• Build tools to improve the lives of our data scientists.
• Contribute to the design and architecture of our ML systems.

What You Bring

• • 5+ years of development experience with a focus on Machine Learning and Engineering roles
  • Strong proficiency in Python and SQL, with experience in machine learning libraries (Pytorch, Tensorflow)
  • Experience with managing the full model production lifecycle, including deployment, release, and post-launch monitoring
  • Experience working with a diverse, cross-disciplinary team to integrate machine learning into product features
  • 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
  • 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

$190-220k base salary

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