MLOps Engineer
Bengaluru, Ind-29, IN, 560035
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign, build, and maintain ML pipelines for model training, evaluation, and AI security testing.
Own infrastructure for experimentation, benchmarking, and large-scale model analysis.
Manage compute, storage, and orchestration environments for research and platform workloads.
From the employer’s posting
Key Responsibilities Design, build, and maintain ML pipelines for model training, evaluation, and AI security testing. Own infrastructure for experimentation, benchmarking, and large-scale model analysis.
Design, build, and maintain ML pipelines for model training, evaluation, and AI security testing. Own infrastructure for experimentation, benchmarking, and large-scale model analysis. Integrate AI security checks (e.g., scanning, verification, unlearning workflows) into ML pipelines.
Integrate AI security checks (e.g., scanning, verification, unlearning workflows) into ML pipelines. Manage compute, storage, and orchestration environments for research and platform workloads. Ensure reproducibility, traceability, and auditability of models, data, and experiments.
What you’ll bring
All qualificationsCore experience
- Experience: - 5–8+ years of experience in MLOps, ML infrastructure, or platform engineering roles.
Qualification wording
Experience: - 5–8+ years of experience in MLOps, ML infrastructure, or platform engineering roles. - Proven experience supporting ML research or production ML systems at scale.
Education & alternatives
Qualifications & Experience Education: - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Experience: - 5–8+ years of experience in MLOps, ML infrastructure, or platform engineering roles. - Proven experience supporting ML research or production ML systems at scale.
Tools in this posting
- Python
- Docker
- Kubernetes
Source — Tool mentions in context
Required Technical Skills - Strong experience with MLOps platforms, ML pipelines, and workflow orchestration tools. - Hands-on experience with containerisation and orchestration (Docker, Kubernetes, or equivalent). - Experience managing cloud or on-prem compute environments for ML workloads. - Familiarity with experiment tracking, model registries, and data versioning tools. - Understanding of security, compliance, and access control considerations in ML systems. - Strong scripting and programming skills (Python preferred). Qualifications & Experience
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 28, 2026 · today
- Recorded sightings
- 10
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on careers.wipro.com. The employer’s form will show what is required.
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Job description
Job Description
The MLOps / Infrastructure Engineer – AI Security is responsible for building, operating, and scaling the infrastructure and ML pipelines that support AI security research and production systems. The role ensures that AI models, datasets, experiments, and security evaluations are reproducible, observable, and deployable in a secure and compliant manner.
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Key Responsibilities
- Design, build, and maintain ML pipelines for model training, evaluation, and AI security testing.
- Own infrastructure for experimentation, benchmarking, and large-scale model analysis.
- Integrate AI security checks (e.g., scanning, verification, unlearning workflows) into ML pipelines.
- Manage compute, storage, and orchestration environments for research and platform workloads.
- Ensure reproducibility, traceability, and auditability of models, data, and experiments.
- Support deployment, monitoring, and lifecycle management of AI security tools and services.
- Collaborate with research, backend, and security teams to enable end-to-end delivery.
Required Technical Skills
- Strong experience with MLOps platforms, ML pipelines, and workflow orchestration tools.
- Hands-on experience with containerisation and orchestration (Docker, Kubernetes, or equivalent).
- Experience managing cloud or on-prem compute environments for ML workloads.
- Familiarity with experiment tracking, model registries, and data versioning tools.
- Understanding of security, compliance, and access control considerations in ML systems.
- Strong scripting and programming skills (Python preferred).
Qualifications & Experience
Education:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Experience:
- 5–8+ years of experience in MLOps, ML infrastructure, or platform engineering roles.
- Proven experience supporting ML research or production ML systems at scale.
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Mandatory Skills: Cloud Security Engineering .
Experience: 8-10 Years .
Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention.
Source details
Source notes
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- Pay
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- Location & working pattern
Bengaluru, Ind-29, IN, 560035
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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