Telangana Senior devops engineer Jobs – 83 Open Jobs Today

Senior / Lead ML Engineer (Databricks MLOps)
Anblicks —Hyderabad, Telangana
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- Master's degree
Quick apply
Sr. Devops Engineer
Altostratus Solutions —Hyderabad, Telangana
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CACI Limited —Madhapur, Hyderabad, Telangana
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Infor —Hyderabad, Telangana
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Fournine Cloud Solutions —Hyderabad, Telangana
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Zetamicron —Hyderabad, Telangana
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Sr. DevOps Engineer
Techblocks —Hyderabad, Telangana
- Full-time
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- APIs
- Linux
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Senior Release Engineering
Veeva Systems —Hyderabad, Telangana
- Full-time
- Computer Science
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Deputy Director - DevSecOps
PepsiCo —Hyderabad, Telangana
- Remote
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DevOps Lead
MostEdge —Hyderabad, Telangana
- Full-time
- Computer Science
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- Master's degree
- Paid sick time
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Teradata —Hyderabad, Telangana
- Full-time
- Hybrid work
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SR. DEVOPS ENGINEER (PurpleWave)
Copart —Hyderabad, Telangana
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Junior Salesforce DevOps Engineer
LSEG (London Stock Exchange Group) —Hyderabad, Telangana
- Full-time
- Salesforce
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Senior DevOps Engineer
NCR Atleos —Hyderabad, Telangana
- Full-time
- Azure
- DevOps
- Java
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2d
Sr. Software Engineer - DevOps
Jarus Technologies —Ecil, Hyderabad, Telangana
- Email
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TCPWave —Hyderabad, Telangana
Devops Engineer
Capco —Hyderabad, Telangana
- DevOps
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- Analysis skills
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1d
DevOps Engineer, IN
DAZN —Hyderabad, Telangana
- Full-time
- Azure
- DevOps
- AWS
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DevOps Engineer - Sr - Team Lead
Anblicks —Hyderabad, Telangana
- DevOps
Quick apply
Senior Staff Engineer, DevOps
Nagarro —Hyderabad, Telangana
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Senior / Lead ML Engineer (Databricks MLOps)

Anblicks -
Hyderabad, Telangana

Quick apply

Job details

Qualifications

CI/CD
Azure
Law
Kubernetes
Software deployment
DevOps
Spark
Git
Master's degree
Databases
AWS
Docker
Terraform
Continuous integration
Mentoring
Unity
GitHub
AI
Jenkins
Communication skills
Python

Full job description

Job Role: Senior Or Lead –MLOps Engineer (Databricks)

Location: Hyderabad (Hybrid)

Experience: 8 Years+

Company: Anblicks

Role Overview

Anblicks is hiring a Senior Level MLOps Engineer with Expertise in Databricks to drive the design, implementation, and scaling of enterprise-grade ML platforms. This role is ideal for a hands-on leader who can own end-to-end MLOps strategy and execution, while mentoring teams and delivering production-ready ML systems on Databricks.

You will play a key role in building scalable, reliable, and automated ML pipelines, enabling faster experimentation, deployment, and monitoring of models across business use cases.

Key Responsibilities

MLOps Leadership & Architecture

- Lead the design and implementation of scalable MLOps frameworks on Databricks
- Define and enforce best practices, standards, and governance for ML lifecycle management
- Architect end-to-end ML pipelines covering data ingestion, feature engineering, training, deployment, and monitoring
- Drive platform standardization for model development and operationalization

Databricks & Platform Engineering

- Build and optimize solutions using Databricks ecosystem: MLflow, Unity Catalog, Workflows, Delta Lake, Mosaic AI
- Develop high-performance Spark-based pipelines for large-scale data processing
- Enable model versioning, experiment tracking, and reproducibility
- Ensure scalability, security, and performance of ML platforms

MLOps & DevOps Integration

- Implement CI/CD pipelines for ML workflows using GitHub Actions, Jenkins, Terraform, or similar tools
- Automate model deployment, monitoring, and retraining pipelines
- Work with containerization and orchestration tools like Docker and Kubernetes
- Establish observability and monitoring frameworks for ML systems

Advanced AI / GenAI Enablement (Good to Have)

- Support development of LLM-based and GenAI solutions
- Build RAG pipelines and integrate LLMs into enterprise workflows
- Evaluate and onboard tools like OpenAI, Bedrock, Vertex AI, LangGraph

Stakeholder Collaboration

- Collaborate with Data Scientists, Data Engineers, and Product Teams to productionize ML use cases
- Translate business requirements into scalable ML solutions
- Provide technical leadership, mentorship, and code reviews

Required Skills & Experience

- 7–12 years of experience in ML Engineering / MLOps / Data Engineering
- Strong hands-on experience with Databricks (must-have)
- Expertise in MLflow, Unity Catalog, Workflows, Delta Lake
- Strong programming skills in Python (mandatory)
- Experience with Apache Spark and distributed data processing
- Solid understanding of ML lifecycle and model deployment strategies
- Experience with CI/CD and DevOps practices
- Hands-on experience with Airflow, Kubeflow, or similar orchestration tools
- Experience working with AWS / Azure / GCP cloud platforms

Preferred Qualifications

- Databricks Certification (Associate / Professional / Architect)
- Experience with GenAI / LLM ecosystems
- Familiarity with vector databases (Pinecone, ChromaDB, etc.)
- Experience with Docker, Kubernetes, and infrastructure as code (Terraform)
- Exposure to model monitoring and observability tools

Leadership & Behavioral Competencies

- Strong ownership mindset with the ability to lead from the front
- Excellent problem-solving and analytical thinking
- Ability to manage multiple priorities in a fast-paced environment
- Strong communication skills with both technical and business stakeholders

Why Join Anblicks

- Work on cutting-edge Databricks and AI/ML platforms
- Opportunity to lead enterprise-scale ML transformations
- Collaborative and innovation-driven engineering culture
- Exposure to modern data + AI ecosystem (Snowflake, Databricks, GenAI)

Quick apply

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