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
Drive continuous improvement and innovation in ML practices
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
Mentorship experience and team collaboration skills
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)
