Time since we first saw it
Day 28
Similar jobs usually come down between day 6 and day 70.
At Brillio-2, jobs usually come down by about day 25.
From 4,523 similar postings that came down, and 58 of Brillio-2’s. Coming down is not always a hire.
Senior AI/ML Engineer
Bangalore, Karnataka, India
Live, first seen by us 28 days ago- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingLead design and architecture of enterprise-scale AI platforms
Define frameworks for model lifecycle, MLOps/LLMOps, and AI observability
Establish Responsible AI principles, governance, and technical guardrails
Define reusable architecture patterns and reference models for AI and GenAI
Maintain AI model governance, version control, and documentation
From the employer’s posting
Lead the design and architecture of enterprise-scale AI platforms
Define and implement frameworks for model lifecycle management, MLOps/LLMOps, and AI observability
Establish and enforce Responsible AI principles, governance frameworks, and technical guardrails across AI solutions
define reusable architecture patterns, standards, and reference models for AI and GenAI solutions
Maintain and improve AI model governance, version control, and documentation
What you’ll bring
All qualificationsCore experience
- Expertise in enterprise-scale AI platform design and operationalization
- Experience with cloud-based AI platforms and modern data/AI architectures
- Experience with Great Expectations and Evidently AI for model validation
- Deep proficiency in model lifecycle management, MLOps/LLMOps, and AI observability
- Knowledge of Responsible AI, AI governance, model risk, security, and compliance
- Strong proficiency in regression analysis (linear and logistic)
Preferred experience
- Experience with GenAI architectures, large language models, and AI agents
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
- Proficiency in advanced ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, or MXNet
- Knowledge of vector databases and AI orchestration
Qualification wording
Expertise in enterprise-scale AI platform design and operationalization
Experience with cloud-based AI platforms and modern data/AI architectures
Experience with Great Expectations and Evidently AI for model validation
Deep proficiency in model lifecycle management, MLOps/LLMOps, and AI observability
Knowledge of Responsible AI, AI governance, model risk, security, and compliance
Strong proficiency in regression analysis (linear and logistic)
Experience with GenAI architectures, large language models, and AI agents
Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
Proficiency in advanced ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, or MXNet
Knowledge of vector databases and AI orchestration
Education & alternatives
Desired Qualifications: - Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline - Certification in Machine Learning or Data Science (e.g., TensorFlow Developer Certificate, Microsoft Certified: Azure AI Engineer Associate)
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 8, 202628 days ago
- Recorded sightings
- 71
- Last seen by us
- Nov 6, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Brillio-2 is hiring
46 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring is steady
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SAS
- Azure
- Keras
- PySpark
- PyTorch
- TensorFlow
- Great Expectations
Where the posting names them
- Deep proficiency in model lifecycle management, MLOps/LLMOps, and AI observability - Advanced programming skills in Python and PySpark - Experience with cloud-based AI platforms and modern data/AI architectures
- Certification in Machine Learning or Data Science (e.g., TensorFlow Developer Certificate, Microsoft Certified: Azure AI Engineer Associate) - Relevant certification in statistical analysis or advanced analytics (e.g., SAS Certified Specialist, IBM Data Science Professional Certificate) Employment type
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline - Certification in Machine Learning or Data Science (e.g., TensorFlow Developer Certificate, Microsoft Certified: Azure AI Engineer Associate) - Relevant certification in statistical analysis or advanced analytics (e.g., SAS Certified Specialist, IBM Data Science Professional Certificate)
- Experience with GenAI architectures, large language models, and AI agents - Proficiency in advanced ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, or MXNet - Knowledge of vector databases and AI orchestration
- Competence in classification algorithms such as decision trees and SVM - Experience with Great Expectations and Evidently AI for model validation - Strong proficiency in regression analysis (linear and logistic)
Your next step
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Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Senior AI/ML Engineer
Job requirements
- Lead the design and architecture of enterprise-scale AI platforms, ensuring scalability, security, and operational readiness
- Define and implement frameworks for model lifecycle management, MLOps/LLMOps, and AI observability to support robust deployment and monitoring
- Establish and enforce Responsible AI principles, governance frameworks, and technical guardrails across AI solutions
- Drive platform-level technical decision-making and define reusable architecture patterns, standards, and reference models for AI and GenAI solutions
- Collaborate with business, data, technology, and platform teams to translate AI architecture principles into production-ready capabilities
- Evaluate emerging AI technologies and assess their applicability to enterprise AI platforms, supporting long-term scalability and business outcomes
- Maintain and improve AI model governance, version control, and documentation for ongoing operational excellence
- Expertise in enterprise-scale AI platform design and operationalization
- Deep proficiency in model lifecycle management, MLOps/LLMOps, and AI observability
- Advanced programming skills in Python and PySpark
- Experience with cloud-based AI platforms and modern data/AI architectures
- Knowledge of Responsible AI, AI governance, model risk, security, and compliance
- Hands-on experience with KubeFlow and BentoML for ML pipeline orchestration
- Competence in classification algorithms such as decision trees and SVM
- Experience with Great Expectations and Evidently AI for model validation
- Strong proficiency in regression analysis (linear and logistic)
- Statistical analysis and computing for large datasets
- Experience with GenAI architectures, large language models, and AI agents
- Proficiency in advanced ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, or MXNet
- Knowledge of vector databases and AI orchestration
- Understanding of AI observability and Responsible AI frameworks
- Experience developing reusable AI architecture patterns and accelerators
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
- Certification in Machine Learning or Data Science (e.g., TensorFlow Developer Certificate, Microsoft Certified: Azure AI Engineer Associate)
- Relevant certification in statistical analysis or advanced analytics (e.g., SAS Certified Specialist, IBM Data Science Professional Certificate)
Experience Range: with at least 6 years of experience in AI/ML engineering, including hands-on expertise in designing, building, and operationalizing enterprise-scale AI platforms Key Responsibilities:
Required Skills:
Preferred Skills:
Desired Qualifications:
Employment type
Employee
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Bangalore, Karnataka, India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.