01
MLOps
Required
TRPD-26-04185
MLOps Engineer
Hiring a senior MLOps Engineer (6–10 years) in Bengaluru for a permanent role to design, deploy, and optimize production-grade ML pipelines. The role sits between Data Science and Enterprise Operations, combining hands-on ML/LLM enablement with cloud ML platforms, workflow orchestration, containerization, and infrastructure automation to improve overall MLOps maturity.
Position summary
- Location
- India
- Workplace
- On-site
- Employment
- Full Time
- Experience
- Minimum 6 years and Maximum 10 years
Role overview
Why This Role Matters.
Hiring a senior MLOps Engineer (6–10 years) in Bengaluru for a permanent role to design, deploy, and optimize production-grade ML pipelines. The role sits between Data Science and Enterprise Operations, combining hands-on ML/LLM enablement with cloud ML platforms, workflow orchestration, containerization, and infrastructure automation to improve overall MLOps maturity.
Your Impact
Deliver Enterprise Value
Help organisations solve complex business problems through modern technology, consulting expertise and measurable outcomes.
Collaboration
Work Across Teams
Collaborate with consultants, architects, engineers and client stakeholders throughout the project lifecycle.
Growth
Learn Continuously
Gain exposure to enterprise technologies, certifications, mentoring and real-world project experience.
Career Path
Grow With Ubique
Build a long-term consulting career with opportunities to take on greater responsibility and leadership over time.
Responsibilities
What You'll Be Doing.
Every role at Ubique contributes directly to solving meaningful business challenges for our clients.
Technology stack
Tools & Technologies.
The platforms and technologies you'll use to build modern, enterprise-grade solutions.
02
Machine Learning Pipelines
Required
03
GCP Vertex AI
Required
04
Vertex AI
Required
05
AWS SageMaker
Required
06
SageMaker
Required
07
Azure ML Studio
Required
08
Azure Machine Learning
Required
09
Apache Airflow
Required
10
Airflow
Required
11
Kubeflow
Required
12
Docker
Required
13
Kubernetes
Required
14
Terraform
Required
15
Python
Required
16
Bash
Required
17
LangChain
Required
18
RAG
Required
19
Retrieval Augmented Generation
Required
20
Vector Database
Required
Requirements
Skills & Experience.
We value curiosity, collaboration and continuous learning. If you don't meet every requirement but believe you can make an impact, we'd still love to hear from you.
Essential
Required Qualifications
MLOps engineering (production ML pipelines)
Cloud ML platforms (GCP Vertex AI and/or AWS SageMaker and/or Azure ML Studio)
Workflow orchestration (Apache Airflow and/or Kubeflow)
Containerization (Docker)
Kubernetes
Infrastructure as Code (Terraform)
Python
Bash
Preferred
Nice to Have
AI/LLM ecosystem experience (LangChain)
RAG frameworks
Vector databases
What you'll gain
More Than Just A Job.
We're committed to helping every team member grow professionally, personally and technically while working on meaningful projects.
Global Exposure
Collaborate with international clients and multicultural teams on enterprise programmes.
Continuous Learning
Expand your expertise through mentoring, certifications and hands-on project experience.
Career Growth
Take ownership, develop leadership skills and grow your consulting career over time.
Flexible Working
Hybrid and remote collaboration designed around trust and delivering exceptional outcomes.
People First
Join a supportive culture where collaboration, respect and long-term relationships come first.
Enterprise Projects
Work on meaningful technology initiatives for leading organisations across industries.
Apply
Apply for MLOps Engineer
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