The Role
Establishes and operates the MLOps foundation for model training, deployment, monitoring, versioning, governance, and reproducibility. Builds model CI/CD pipelines, integrates tooling with lakehouse and Snowflake workflows, manages development and production environments, and supports future agentic AI capabilities. Requires end-to-end MLOps setup experience, container orchestration expertise, and familiarity with Azure ML or equivalent platforms.
Summary Generated by Built In
Phase: Initial phase setup, scaling with later phases
Required experience: 6+ years in ML / DevOps, with 3+ years dedicated MLOps setup and operations.
Role summary
Sets up and configures the MLOps foundation so that models can be trained, deployed, monitored, and governed on top of the data platform. Establishes the tooling and pipelines that later phases, including agentic AI, will depend on.
Key responsibilities
- Set up and configure the MLOps platform and CI/CD for models.
- Build pipelines for model training, deployment, versioning, and monitoring.
- Integrate MLOps tooling with the lakehouse and feature data.
- Establish model governance, lineage, and audit trails.
- Support reproducibility and environment management across dev and production.
- Prepare the MLOps foundation to support agentic AI capabilities in later phases.
Must-have skills and experience
- Proven MLOps setup and configuration experience end to end.
- Experience with model CI/CD, versioning, and monitoring in production.
- Familiarity with Azure ML or equivalent, and readiness for Snowflake-based workflows.
- Containerization and orchestration experience (Docker, Kubernetes).
- Strong understanding of model governance and reproducibility.
Nice to have
- Feature store experience.
- Exposure to agentic AI or LLM operations.
- Infrastructure-as-code experience.
Relevant stack
Azure ML / MLflow or equivalent, Docker, Kubernetes, CI/CD tooling, integrated with the lakehouse and Snowflake.
General attributes
- Proactive and self-driven, able to take ownership and move work forward without waiting to be told.
- AI-enabled in day-to-day work, comfortable using AI tools and copilots to accelerate delivery and quality.
- Strong self-learner who stays current with evolving tools, platforms, and practices.
- Good team player who collaborates well across engineering, operations, and stakeholder groups.
Skills Required
- 6+ years of experience in machine learning or DevOps
- 3+ years dedicated to MLOps setup and operations
- End-to-end MLOps platform setup and configuration experience
- Production experience with model CI/CD, versioning, and monitoring
- Familiarity with Azure ML or an equivalent platform
- Readiness for Snowflake-based workflows
- Containerization and orchestration experience with Docker and Kubernetes
- Strong understanding of model governance and reproducibility
- Feature store experience
- Exposure to agentic AI or LLM operations
- Infrastructure-as-code experience
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The Company
What We Do
Coditude stands out as a rapidly growing force in the digital realm, offering straightforward, impactful tech capabilities. Our team, both seasoned and savvy, is the perfect ally to thrive in the digital age. We excel in Product Development, SaaS Solutions, Enterprise Mobile Applications, AI, Cloud Solutions, Browser Extension Development, and Digital Commerce Solutions, not to mention our prowess in Infrastructure Modernization and Management
