The company is looking to bridge the gap between data science and production systems by operationalizing AI models and making them scalable, reliable, and easy to deploy.
Requirements
- Advanced Python skills—comfortable writing production-grade code and APIs
- Strong AWS knowledge, especially Lambda, EKS, IAM, and cost optimization
- Experience with Databricks or similar platforms (e.g., SageMaker, Spark)
- Hands-on with Terraform and CI/CD automation tools
- Familiar with container orchestration (Kubernetes) and serverless architecture
- Observability skills using DataDog or similar tools
- 5+ years in DevOps, MLOps, or Cloud Engineering with production ML deployment experience
Responsibilities
- Deploy and manage AI/ML models in production using modern MLOps practices
- Build and optimize serverless pipelines using AWS Lambda, moving toward containerized EKS solutions
- Support ML workflows on Databricks and other data processing platforms
- Write robust Python code to support training, inference, and data transformation
- Automate CI/CD for model delivery using GitHub and IaC tools
- Improve observability of model performance and pipeline health with DataDog
- Ensure scalable, secure, and cost-efficient infrastructure for ML systems
Other
- Clear communicator with a collaborative, mentoring mindset
- On-call participation may be required to support production systems
- Hybrid role with in-person collaboration opportunities
- Comprehensive medical, dental, and vision benefits, including a company Health Savings Account contribution
- 401(k): ModMed provides a matching contribution each payday of 50% of your contribution deferred on up to 6% of your compensation
- Generous Paid Time Off and Paid Parental Leave programs
