Principal AIML Operations Engineer

About Madrigal:
Madrigal is a biopharmaceutical company pursuing novel therapeutics for non-alcoholic steatohepatitis (NASH), also known as metabolic dysfunction associated steatohepatitis (MASH). Our first therapy, Rezdiffra (resmetirom), was granted accelerated approval by the U.S. Food and Drug Administration (FDA) for the treatment of adults with NASH with moderate to advanced liver fibrosis (consistent with stages F2 to F3 fibrosis) and is being studied in a Phase 3 trial for the treatment of NASH with compensated cirrhosis.
Role Overview:
Madrigal Pharmaceuticals is a leader in leveraging cutting-edge technology and scientific discovery to bring transformative therapies to market. We are committed to advancing medicine through the innovative application of Artificial Intelligence, Data Science, and Cloud technologies.
As part of our ongoing growth, we are seeking an AIML DevOps Engineer with expertise in Azure Cloud, the Databricks platform, and DevOps practices to join our dynamic Data Science and AI team. This is a unique opportunity to drive impact through automation, scalability, and high-performance cloud solutions.
Position Responsibilities: 
Technical Leadership and Strategy:

• Lead the implementation of scalable AI/ML cloud architectures using Azure, setting the standard for reliability, security, and performance.
• Establish best practices in cloud infrastructure and DevOps methodologies, fostering a culture of continuous improvement and technical excellence.

Solution Architecture and Design:

• Design and deploy Databricks workspaces and clusters to support large-scale data science and AI workloads.
• Architect end-to-end CI/CD pipelines for AI/ML model deployment, utilizing tools like Jenkins, GitLab CI, or Azure DevOps to automate testing and delivery.
• Optimize the deployment of containerized applications using Docker and Kubernetes, ensuring solutions are portable and scalable across environments.

Cross-Functional Collaboration:

• Collaborate with data scientists, Gen AI engineers, and software developers to streamline the development and deployment of AI/ML models.
• Serve as a bridge between the infrastructure, data science, and software teams to align technical implementations with business requirements.
• Contribute to code reviews, share technical insights, and mentor junior engineers within the AI & Data Science team.

Continuous Learning and Innovation:

• Stay updated on advancements in Azure, Databricks, and DevOps technologies, applying them to improve development and deployment processes.
• Proactively identify opportunities for automation and process enhancements within the AI/ML workflows.
• Participate in internal workshops and seminars to promote a learning culture, ensuring the team is abreast of the latest industry trends and best practices.

Qualifications and Skills Required:
Required:

• Bachelor’s degree in Computer Science, Information Technology, or a related field; Master’s degree preferred.
• 10+ years of experience in DevOps, Cloud Engineering, or a similar role, with a focus on AI/ML workflows and data engineering.
• Strong hands-on experience with Azure Cloud, including Infrastructure as Code (IaC) tools such as Terraform or Azure Resource Manager (ARM).
• Proven expertise in managing Databricks environments for data processing and AI workloads.
• Proficiency in CI/CD tools like Jenkins, GitLab CI, or Azure DevOps, and experience in scripting (Python, Bash, etc.).
• Experience with containerization technologies, such as Docker and Kubernetes, for scalable deployment.
• Strong understanding of cloud security best practices and regulatory compliance.

Preferred:

• Microsoft Azure Certifications (e.g., Azure Solutions Architect, Azure DevOps Engineer Expert), Databricks Certifications, GenAI Certifications.
• Experience in AI/ML model lifecycle management and MLOps.
• Familiarity with Apache Spark, Delta Lake, and distributed computing.
• Knowledge of monitoring tools like Prometheus, Grafana, or Datadog.
• Knowledge of integration platforms as a service (iPaaS) like Boomi, SnapLogic, or Workato.

Compensation:
Base salary is determined by several factors that include, but are not limited to, a successful candidate's qualifications, skills, education, experience, business needs, and market demands. The role may also be eligible for bonus, equity, and comprehensive benefits, which include flexible paid time off (PTO), medical, dental, vision, and life and disability insurance.