Databricks MLOps Engineer - Join our growing community
Xenon7
- Hyderabad, Telangana
- Contract
- Full-time
- Technical Assessment – 2-step technical assessment process that includes an interactive problem-solving test, and a verbal interview about your skills and experience
- Matching you to Opportunity – We explore how your skills align with ongoing projects and innovation tracks
- 6+ years of professional experience in DevOps, DataOps, or MLOps roles
- 3+ years hands-on with Databricks, including Delta Lake, MLflow, and cluster/workflow administration
- Strong experience in CI/CD, infrastructure as code (Terraform, GitOps), and Python-based automation
- Solid understanding of ML lifecycle management, experiment tracking, model registries, and automated deployment pipelines
- Deep knowledge of AWS (EKS, IAM, Lambda, CloudFormation or Terraform) and/or Azure (ADLS, Azure DevOps, ACR)
- Experience working with containerized environments, including Kubernetes and Helm
- Familiarity with data governance and access control frameworks like Unity Catalog
- Strong scripting and programming skills in Python, Shell, and YAML/JSON
- Ecosystem of Opportunity: You'll be part of a growing network where client engagements, thought leadership, research collaborations, and mentorship paths are interconnected. Whether you're building solutions or nurturing the next generation of talent, this is a place to scale your influence.
- Collaborative Environment: Our culture thrives on openness, continuous learning, and engineering excellence. You'll work alongside seasoned practitioners who value smart execution and shared growth.
- Flexible & Impact-Driven Work: Whether you're contributing from a client project, innovation sprint, or open-source initiative, we focus on outcomes—not hours. Autonomy, ownership, and curiosity are encouraged here.
- Talent-Led Innovation: We believe communities are strongest when built around real practitioners. Our Innovation Community isn’t just a knowledge-sharing forum—it’s a launchpad for members to lead new projects, co-develop tools, and shape the direction of AI itself.