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DaVita

Provides dialysis and comprehensive kidney care

AI Technical Senior Lead - IT

Applied Machine LearningConfirmed live in the last 24 hours
Full-time$115k - $183k /yr

About the Job

Requirements

  • A bachelor's or master's degree in computer science, engineering, or a related field is required.
  • Proven experience managing cloud infrastructure, preferably with Google Cloud Platform, Vertex AI, MLOps, and Terraform.
  • Strong understanding of large language models and experience developing and deploying models.
  • Proficiency in Python, Java, or a similar programming language.
  • Familiarity with continuous integration and continuous delivery tools and practices.
  • Familiarity with AutoML platforms such as Vertex AI AutoML, DataRobot, and open-source platforms such as Snorkel and H2O.ai.
  • Google Cloud certifications such as Google Cloud Engineer or Generative AI Leader are a nice-to-have.

Responsibilities

  • Build and maintain enterprise feature stores and real-time data lakes using BigQuery and Pub/Sub to support predictive modeling and natural language processing workflows.
  • Design and implement resilient, secure multi-cloud architectures using Google Cloud Platform, Azure, and Terraform to support highly available AI operations.
  • Operationalize machine learning models using Python, PySpark, and Kafka for batch and real-time inference.
  • Use LangChain, LangGraph, CrewAI, and Vertex AI Agent Builder to develop agentic AI solutions.
  • Integrate secure inference APIs through gateways such as Apigee.
  • Implement end-to-end continuous integration and continuous delivery pipelines for automated model training, deployment, and rollback.
  • Standardize large language model operations and machine learning operations observability using LangSmith and Arize.
  • Coordinate data and machine learning workflows using Cloud Composer (Airflow).
  • Collaborate with data scientists to understand model objectives and translate them into technical specifications, applying suitable foundation models and frameworks to optimize effectiveness, response time, and cost.
  • Deploy AI models into multiple environments using continuous integration and continuous delivery pipelines and integrate them with existing systems.
  • Automate infrastructure provisioning and management using infrastructure as code principles.
  • Establish observability and data governance using Grafana, OpenTelemetry, Splunk, or Arize to monitor pipeline health and model behavior.
  • Evaluate and integrate AI vendors, including Snorkel, H2O.ai, and DataRobot, for scalability, security, and cost efficiency.
  • Ensure deployments comply with Responsible AI and regulatory standards in regulated financial or retail environments.
  • Lead proofs of concept and pilots in controlled lab environments to validate emerging AI technologies.
  • Partner with Data Science, Risk, Security, and Product teams to align AI adoption with business strategy.
  • Provide technical mentorship to offshore and onshore engineering teams and ensure high performance standards and service-level agreement compliance.
  • Create and maintain documentation for infrastructure setups, model development processes, and deployment workflows.
  • Establish and promote best practices for AI management and model development within the team.
  • Implement security measures to protect sensitive data and ensure compliance with industry regulations.
  • Work with security teams to address vulnerabilities and maintain a secure environment for AI operations.

Desired Qualifications

  • Google Cloud Platform, Vertex AI, MLOps, and Terraform experience are strongly preferred.

About the Company

DaVita

Provides dialysis and comprehensive kidney care

DaVita provides kidney care services, primarily dialysis, for people with chronic kidney disease and end-stage renal disease, and runs integrated care programs with educational resources. Its services are delivered through dialysis centers, with treatment guided by patient-centered care and tracked using clinical metrics to monitor outcomes; it also offers Kidney Smart classes and risk quizzes to help patients manage kidney health. The company differentiates itself by focusing on value-based, holistic and equitable care across a network, coordinating services to improve results while controlling costs. Its goal is to improve patient outcomes, reduce healthcare costs, and build a robust, equitable kidney-care community.

Company size
10,001+
Company stage
IPO
Headquarters
Denver, CO
Founded
1979

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