Engineering Group Manager- MLOps
Chennai, India
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingBuild and operate MLOps platforms on AWS supporting autonomous driving ML workloads
Implement and maintain ML pipelines using:
Support CI/CD pipelines for ML code, models, and infrastructure (GitHub‑based)
From the employer’s posting
MLOps Platform & Infrastructure Build and operate MLOps platforms on AWS supporting autonomous driving ML workloads Implement and maintain highly available, multi‑zone training and deployment environments
MLOps Pipelines & Tooling Implement and maintain ML pipelines using: Apache Airflow for orchestration
MLflow for experiment tracking, model versioning, and lifecycle management Support CI/CD pipelines for ML code, models, and infrastructure (GitHub‑based) Ensure ML workflows are:
Tools in this posting
- Kubernetes
- Python
- AWS
- S3
- Terraform
- MLflow
- Airflow
Source — Tool mentions in context
- Troubleshoot and resolve platform‑level issues impacting ML productivity AWS & Kubernetes Operations - Deploy and operate ML workloads using:
- Deploy and operate ML workloads using: - Amazon EKS / Kubernetes - AWS VPCs, subnets, routing, and network isolation
- Multi‑GPU / distributed training (Ray or equivalent) - Kubernetes / EKS - Infrastructure as Code (Terraform)
- Airflow and MLflow - Proficient Python for automation, pipelines, and tooling - Experience building and operating CI/CD pipelines (GitHub)
MLOps Platform & Infrastructure - Build and operate MLOps platforms on AWS supporting autonomous driving ML workloads - Implement and maintain highly available, multi‑zone training and deployment environments
- Amazon EKS / Kubernetes - AWS VPCs, subnets, routing, and network isolation - S3 (including Intelligent‑Tiering) for large‑scale sensor and training data
- S3 (including Intelligent‑Tiering) for large‑scale sensor and training data - AWS Lambda for event‑driven ML and data workflows - AWS IoT resources managed via Terraform
- AWS Lambda for event‑driven ML and data workflows - AWS IoT resources managed via Terraform - Contribute to platform resilience through:
Key ingredients for succeeding in this role are your: - 13+ years experience ,Strong hands‑on experience with AWS for ML workloads - Practical experience with:
- AWS VPCs, subnets, routing, and network isolation - S3 (including Intelligent‑Tiering) for large‑scale sensor and training data - AWS Lambda for event‑driven ML and data workflows
- Kubernetes / EKS - Infrastructure as Code (Terraform) - Airflow and MLflow
- Apache Airflow for orchestration - MLflow for experiment tracking, model versioning, and lifecycle management - Support CI/CD pipelines for ML code, models, and infrastructure (GitHub‑based)
- Infrastructure as Code (Terraform) - Airflow and MLflow - Proficient Python for automation, pipelines, and tooling
- Implement and maintain ML pipelines using: - Apache Airflow for orchestration - MLflow for experiment tracking, model versioning, and lifecycle management
Job description
MLOps Manager
Help shape the future of mobility.
Imagine a world with zero vehicle accidents, zero vehicle emissions, and wireless vehicle connectivity all around us. Every day, we move closer to making that world a reality. Aptiv’s passionate team of engineers and developers creates advanced safety systems, high-performance electrification solutions and data connectivity solutions so that automakers can bring advanced capabilities to more people around the globe. This is how we enable sustainable mobility and help to prevent accidents caused by human error.
Your Role
MLOps Platform & Infrastructure
Build and operate MLOps platforms on AWS supporting autonomous driving ML workloads
Implement and maintain highly available, multi‑zone training and deployment environments
Operate distributed, multi‑GPU training setups (e.g., Ray clusters)
Assist in maintaining infrastructure standards for compute, storage, networking, and security
Troubleshoot and resolve platform‑level issues impacting ML productivity
AWS & Kubernetes Operations
Deploy and operate ML workloads using:
Amazon EKS / Kubernetes
AWS VPCs, subnets, routing, and network isolation
S3 (including Intelligent‑Tiering) for large‑scale sensor and training data
AWS Lambda for event‑driven ML and data workflows
AWS IoT resources managed via Terraform
Contribute to platform resilience through:
Multi‑AZ deployments
Backup, recovery, and fault‑tolerance mechanisms
MLOps Pipelines & Tooling
Implement and maintain ML pipelines using:
Apache Airflow for orchestration
MLflow for experiment tracking, model versioning, and lifecycle management
Support CI/CD pipelines for ML code, models, and infrastructure (GitHub‑based)
Ensure ML workflows are:
Reproducible
Traceable
Auditable (aligned with automotive engineering expectations)
Machine Learning Enablement
Support large‑scale data ingestion and preprocessing pipelines for sensor‑heavy datasets
Implement data validation and data quality checks
Help enforce train / validation / test split governance
Partner with ML engineers to:
Improve training performance
Reduce infrastructure cost
Streamline evaluation and deployment workflows
Collaboration with ML & Autonomous Driving Teams
Work closely with ML engineers and researchers developing:
Perception models (vision, sensor fusion, detection, tracking)
Behavioral and decision‑making systems
Translate ML workloads and requirements into stable, production‑ready pipelines
Adapt ML tooling and infrastructure to the realities of safety‑critical automotive systems
Monitoring, Reliability & Operations
Build and maintain monitoring and logging for:
ML pipelines
Training jobs
Deployed models and infrastructure
Track system health, failures, performance regressions, and operational metrics
Participate in incident response, root cause analysis, and post‑mortems
Continuously improve platform reliability, scalability, and developer experience
Your Background
Key ingredients for succeeding in this role are your:
13+ years experience ,Strong hands‑on experience with AWS for ML workloads
Practical experience with:
Multi‑GPU / distributed training (Ray or equivalent)
Kubernetes / EKS
Infrastructure as Code (Terraform)
Airflow and MLflow
Proficient Python for automation, pipelines, and tooling
Experience building and operating CI/CD pipelines (GitHub)
Machine Learning Foundations
Solid understanding of end‑to‑end ML workflows:
Data ingestion and preprocessing
Data validation and quality controls
Training, evaluation, and deployment
Experience supporting ML teams running large‑scale experiments and production models
Automotive / Autonomous Systems Exposure
Working knowledge of:
Perception systems
Behavioral or decision‑making ML components
Prior experience in automotive, ADAS, or autonomous driving environments
Awareness of constraints related to:
Safety‑critical systems
Real‑time or near‑real‑time performance
Why join us?
You can grow at Aptiv.Aptiv provides an inclusive work environment where all individuals can grow and develop, regardless of gender, ethnicity or beliefs.
You can have an impact. Safety is a core Aptiv value; we want a safer world for us and our children, one with: Zero fatalities, Zero injuries, Zero accidents.
You have support. We ensure you have the resources and support you need to take care of your family and your physical and mental health with a competitive health insurance package.
Your Benefits at Aptiv:
Hybrid and flexible working hours;
Higher Education Opportunities (UDACITY, UDEMY, COURSERA are available for your continuous growth and development);
Life and accident insurance;
Sodexo cards for food and beverages
Well Being Program that includes regular workshops and networking events;
EAP Employee Assistance;
Access to fitness clubs (T&C apply);
Creche facility for working parents;
Apply today, and together let’s change tomorrow!
#LI-NB1
Privacy Notice - Active Candidates: https://www.aptiv.com/privacy-notice-active-candidates
Aptiv is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability status, protected veteran status or any other characteristic protected by law.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on aptiv.wd5.myworkdayjobs.com. The employer’s form will show what is required.
Already applied? Track this application
Source & posting history
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
Chennai, India
Your Benefits at Aptiv: - Hybrid and flexible working hours; - Higher Education Opportunities (UDACITY, UDEMY, COURSERA are available for your continuous growth and development);
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Aug 11, 2026
- Recorded sightings
- 119
- Last seen by us
- Oct 1, 2026
- Employer says posted
- Aug 6, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Report an errorSee how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.