招聘
AI & MLOps Architect – Autonomous Driving
We are seeking an AI & MLOps Architect to design, build, and scale robust, production-grade MLOps infrastructure for L2++ autonomous driving systems operating in complex urban environments.
You will be responsible for end-to-end ML platform architecture on AWS, enabling scalable training, validation, deployment, and observability of perception and behavioral models that meet automotive-grade reliability, safety, and performance standards.
This role sits at the intersection of machine learning engineering, cloud architecture, and automotive AI systems, and requires deep technical leadership across ML training pipelines, infrastructure automation, and multi-region scalability.
Key Responsibilities
MLOps & Cloud Architecture:
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Design and own end-to-end MLOps architecture on AWS for autonomous driving workloads
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Architect multi-zone, highly available ML platforms supporting urban L2++ hands-off use cases
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Build and operate scalable multi-GPU training environments using Ray clusters
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Define infrastructure standards for compute management, networking, storage, and security
AWS Platform & Infrastructure
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Implement and manage:
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Amazon EKS / Kubernetes (K8s) for ML workloads
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VPC architecture, subnets, routing, and network isolation
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S3 Intelligent-Tiering for cost-efficient storage of large-scale sensor and training data
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AWS Lambda for event-driven ML workflows and automation
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AWS IoT infrastructure provisioned via Terraform
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Ensure strong multi-zone resilience, fault tolerance, and disaster recovery strategies
MLOps Pipelines & Tooling
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Design and operate ML pipelines using:
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Apache Airflow for orchestration
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MLflow for experiment tracking, model versioning, and lifecycle management
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Implement CI/CD pipelines for ML and infrastructure using GitHub
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Enable reproducible, traceable, and auditable ML workflows aligned with automotive standards
Machine Learning Engineering
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Enable scalable data ingestion and processing pipelines for sensor-rich datasets
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Establish data quality checks, validation frameworks, and train/test split governance
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Support ML teams with optimized workflows for training, evaluation, and deployment
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Collaborate on best practices for training at scale, including performance tuning and cost optimization
Algorithmic & Domain Collaboration
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Work closely with ML researchers and engineers on:
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Perception algorithms (vision, sensor fusion, object detection, tracking)
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Behavioral and decision-making algorithms
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Translate algorithmic requirements into production-ready infrastructure
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Apply automotive domain knowledge to ensure platform suitability for safety-critical systems
Observability, Scalability & Operations
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Build strong monitoring, logging, and observability for ML systems and infrastructure
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Enable performance metrics, failure detection, and operational insights across the ML lifecycle
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Continuously improve platform scalability, reliability, and operational efficiency
Required Qualifications
Technical Skills:
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Strong experience with AWS cloud architecture for ML workloads
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Hands-on expertise in:
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Multi-GPU training (Ray or equivalent distributed frameworks)
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EKS / Kubernetes
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Infrastructure as Code (Terraform)
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Airflow, MLflow
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Proficient Python programming for ML and platform automation
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Experience building and operating CI/CD pipelines (GitHub-based)
Machine Learning Competence
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Deep understanding of ML training pipelines, including:
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Data ingestion and preprocessing
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Data quality assurance
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Train/test validation strategies
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Experience supporting large-scale ML experimentation and productionization
Automotive & Algorithmic Understanding
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Solid understanding of:
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Perception systems
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Behavioral / decision-making algorithms
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Prior experience in automotive, ADAS, or autonomous driving environments is required
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Familiarity with constraints of safety-critical and real-time systems
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:
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Private health care (Signal Iduna) and Life insurance for you and your beloved ones
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Well-Being Program that includes regular webinars, workshops, and networking events
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Hybrid work (min. 47 days/yr of remote work, flexible working hours)
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Employee Pension Plan paid by the employer (you get + 3,5% on each gross salary)
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Access to sports groups and Multisport card
#Li=DL1
- 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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关于Aptiv

Aptiv
PublicA global technology company that develops safer, greener, and more connected solutions, which enable the future of mobility.
10,001+
员工数
Dublin
总部位置
$10.2B
企业估值
评价
3.8
10条评价
工作生活平衡
2.8
薪酬
3.2
企业文化
3.6
职业发展
3.1
管理层
3.4
68%
推荐给朋友
优点
Supportive management and leadership
Good benefits and vacation time
Professional development opportunities
缺点
Heavy workload and overtime expectations
Fast-paced and stressful environment
Limited growth opportunities
薪资范围
56个数据点
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0份报告
$67,909
年薪总额
基本工资
$27,164
股票
$33,955
奖金
$6,791
$47,536
$88,282
面试经验
4次面试
难度
3.8
/ 5
时长
14-28周
体验
正面 0%
中性 0%
负面 100%
面试流程
1
Application Review
2
Resume Review
3
Recruiter Screen
4
Phone Interview
5
Final Interview
6
Offer Decision
常见问题
Behavioral/STAR
Past Experience
Culture Fit
Industry Knowledge
Leadership Scenarios
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