Remote MLOps Lead — AI Deployment & Ops

Intermountain Healthcare Inc.; Topeka (KS); Remoto; USD 82.000 - 127.000; Tempo pieno

Vantaggi offerti da questo lavoro

Generous benefits package

AP4P pay-for-performance

Descrizione del lavoro

Intermountain Health (SelectHealth) is seeking a Machine Learning Operations Manager to lead and scale enterprise ML deployments. You will manage a diverse team of ML, data, and software engineers, driving the roadmap for MLOps while upholding responsible AI practices.

You will mentor engineers, collaborate with executives, and deliver solutions that reduce costs and improve member outcomes. The role is fully remote with periodic travel and a competitive compensation package.

Competenze

• Proven experience delivering ML ops infrastructure and solutions.
• CI/CD with Docker, Kubernetes; IaC with Terraform.
• Experience with Databricks Asset Bundles.
• Strong leadership and stakeholder communication.
• Knowledge of ML methodologies and agentic systems.
• Proficiency in Python, R, SQL.
• Experience with Spark, TensorFlow, MLFlow, LangChain.

Mansioni

• Set strategic direction for the MLOps stack and drive architecture decisions.
• Lead AI/ML, data, software eng, and cloud ops teams; align with business goals.
• Ensure responsible AI practices in monitoring and governance.
• Oversee roadmap execution and project delivery across ML operations.
• Mentor engineers and foster a high-performing culture.
• Collaborate with stakeholders to deploy enterprise ML solutions.

Conoscenze

Machine Learning Operations

Cloud Platforms

Artificial Intelligence

Team Leadership

CI/CD Best Practices

Formazione

Bachelor's degree in AI, ML, CS, Statistics, or related field

Strumenti

Docker

Kubernetes

Terraform

Databricks Asset Bundles

Spark

TensorFlow

MLFlow

LangChain

Descrizione del lavoro

Intermountain Health (SelectHealth) is seeking a Machine Learning Operations Manager to lead and scale enterprise ML deployments. You will manage a diverse team of ML, data, and software engineers, driving the roadmap for MLOps while upholding responsible AI practices.

You will mentor engineers, collaborate with executives, and deliver solutions that reduce costs and improve member outcomes. The role is fully remote with periodic travel and a competitive compensation package.