Databricks MLOps Engineer

6 days ago


Hyderabad, Telangana, India Xenon7 Full time ₹ 15,00,000 - ₹ 30,00,000 per year

About us:

Where elite tech talent meets world-class opportunities

At Xenon7, we work with leading enterprises and innovative startups on exciting, cutting-edge projects that leverage the latest technologies across various domains of IT including Data, Web, Infrastructure, AI, and many others. Our expertise in IT solutions development and on-demand resources allows us to partner with clients on transformative initiatives, driving innovation and business growth. Whether it's empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today's most complex challenges.

We are building a community of top-tier experts and we're opening the doors to an exclusive group of exceptional AI & ML Professionals ready to solve real-world problems and shape the future of intelligent systems.

Structured Onboarding Process

We ensure every member is aligned and empowered:

  1. Screening – We review your application and experience in Data & AI, ML engineering, and solution delivery
  2. Technical Assessment – 2-step technical assessment process that includes an interactive problem-solving test, and a verbal interview about your skills and experience
  3. Matching you to Opportunity – We explore how your skills align with ongoing projects and innovation tracks

Who We're Looking For

We're looking for a Senior MLOps Engineer with deep expertise in the Databricks ecosystem to help us build and scale reliable, secure, and automated ML platforms across enterprise environments. You'll work closely with data scientists, ML engineers, DevOps teams, and cloud architects to implement and maintain production-grade machine learning infrastructure using best practices in MLOps, CI/CD, and cloud-native services.

This is a hands-on technical leadership role ideal for engineers who can work across the entire ML lifecycle—from experiment tracking to scalable deployment—while championing automation, governance, and performance.

If you're driven by curiosity and eager to influence how AI shapes the future, this is your platform.

Requirements

  • 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

Benefits

At Xenon7, we're not just building AI systems—we're building a community of talent with the mindset to lead, collaborate, and innovate together.

  • 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.

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