We are expanding our team and looking for an experienced AIML DevOps Engineer with a strong background in Azure Cloud, Databricks, and DevOps methodologies to join our vibrant Data Science and AI team. This position offers an exciting opportunity to make a significant impact by driving automation, scalability, and delivering high-performance cloud-based solutions.
Role Responsibilities
Technical Leadership and Strategy :
- Spearhead the development of scalable AI / ML cloud architectures on Azure, ensuring the highest standards of reliability, security, and performance.
- Define and implement cloud infrastructure best practices, alongside DevOps strategies, to cultivate a culture focused on continuous technical improvement and excellence.
Solution Architecture and Design :
Design and deploy Databricks workspaces and clusters to enable efficient data science and AI workloads at scale.Architect robust CI / CD pipelines for seamless AI / ML model deployment using tools like Jenkins, GitLab CI, or Azure DevOps, with an emphasis on automating testing and delivery.Optimize the deployment of containerized applications through Docker and Kubernetes, ensuring portability and scalability across environments.Collaboration Across Teams :
Partner with data scientists, Gen AI engineers, and software developers to enhance the development and deployment processes of AI / ML models.Act as a liaison between the infrastructure, data science, and software teams to align technical solutions with business needs.Contribute to code reviews, offer technical guidance, and mentor junior engineers within the AI & Data Science team.Continuous Improvement and Innovation :
Stay informed on the latest advancements in Azure, Databricks, and DevOps technologies, and integrate these innovations to optimize development and deployment workflows.Proactively identify opportunities to automate and streamline processes within the AI / ML pipeline.Lead internal workshops and knowledge-sharing sessions to promote a culture of continuous learning and ensure the team remains current with industry trends and best practices.Required Qualifications and Skills :
Bachelor's degree in Computer Science, Information Technology, or a related field; a Master's degree is preferred.10 years of experience in DevOps, Cloud Engineering, or a related role, with specific expertise in AI / ML workflows and data engineering.Extensive hands-on experience with Azure Cloud, including familiarity with Infrastructure as Code (IaC) tools like Terraform or Azure Resource Manager (ARM).Proven ability in managing Databricks environments for AI and data processing workloads.Proficiency in CI / CD tools such as Jenkins, GitLab CI, or Azure DevOps, and experience with scripting languages (Python, Bash, etc.).Strong experience with containerization technologies like Docker and Kubernetes for scalable deployments.Solid understanding of cloud security best practices and regulatory requirements.Preferred Qualifications :
Microsoft Azure certifications (e.g., Azure Solutions Architect, Azure DevOps Engineer Expert), Databricks certifications, or GenAI certifications.Expertise in AI / ML model lifecycle management and MLOps.Familiarity with Apache Spark, Delta Lake, and distributed computing environments.Experience with monitoring tools like Prometheus, Grafana, or Datadog.Knowledge of integration platforms as a service (iPaaS) such as Boomi, SnapLogic, or Workato.This position offers a unique chance to contribute to cutting-edge AI and data solutions, making a tangible impact on the team's growth and success.
