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Engineering Group Manager- MLOps

Chennai, India

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What you’ll work on

Full posting
  • Build 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

View original posting ↗

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.

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Source & posting history

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Pay

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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);
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Status in our records
Active
First seen by us
Aug 11, 2026
Recorded sightings
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Last seen by us
Oct 1, 2026
Employer says posted
Aug 6, 2026

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