Senior AWS AI & MLOps Engineer

Aptiv β€” Poland Β· Posted ~1 day ago

Senior

Skills

AWS MLOps machine learning engineering cloud architecture ML platform architecture infrastructure automation ML training pipelines deployment observability multi-region scalability machine learning cloud infrastructure

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Summary

An advanced mobility technology organisation is hiring a senior engineer to design and own an AWS-based MLOps platform for autonomous systems. You will build scalable training, validation, deployment, and observability infrastructure while ensuring demanding reliability, safety, and performance standards.

Highlights

Lead the architecture and operation of an end-to-end MLOps platform on AWS for advanced autonomous-driving workloads. The role combines cloud architecture, machine learning infrastructure, automation, scalability, and high reliability in a technically demanding environment.

Description

At APTIV we shape the future of mobility: we design, develop, and validate systems to improve safety and comfort in vehicles. Come and join the team of skilled development engineers to design, build and scale an MLOps infrastructure for L2++ autonomous driving systems operating in complex urban environments. In this role you will be responsible for an end-to-end ML platform architecture on AWS. The goal is to enable 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 cloud operations, machine learning engineering, and drive automation systems. Let’s be honest: it requires deep technical leadership across ML training pipelines, infrastructure automation, and multi-region scalability. Your new role: MLOps & Cloud Architecture: Design and own end-to-end MLOps architecture on AWS for autonomous driving workloads Build and operate a scalable multi-GPU training environments using Ray clusters AWS Platform & Infrastructure: Implement and manage: Amazon EKS / Kubernetes (K8s), VPC architecture, S3 Intelligent-Tiering, AWS Lambda, and AWS IoT infrastructure provisioned via Terraform MLOps Pipelines & Tooling: Design and operate ML pipelines using Apache Airflow and MLflow Implement CI/CD pipelines for ML and infrastructure using GitHub Algorithmic & Domain Collaboration: Work closely with ML engineers on perception algorithms and decision-making algorithms Observability, Scalability & Operations: Build strong monitoring, logging, and observability systems and infrastructure Enable performance metrics, failure detection, and operational insights across the ML lifecycle Identify root causes of issues and rectify them Engage and communicate with leaders within global development teams Be exposed to OEM customers via remote meetings, in-person demonstrations and presentations Your Background: MSc degree + 4 years of relevant experience or PhD degree in Computer Science, Data Science Strong experience with AWS cloud architecture for ML workloads Hands-on experience in:Multi-GPU training (Ray or equivalent distributed frameworks) Amazon EKS / Kubernetes for ML workloads Infrastructure as Code (Terraform) Airflow, MLflow Proficiency in software development using Python for ML and platform automation Experience building and operating CI/CD pipelines (GitHub-based) Deep understanding of ML training pipelines, including:Data ingestion and preprocessing Data quality assurance Train/test validation strategies Experience supporting large-scale ML experimentation and productionization Familiarity with constraints of safety-critical and real-time systems Excellent problem solving and debugging skills Fluent command in spoken and written English Any of the following will be highly beneficial: Past experience with L2/L2+/L2++ ADAS or autonomous driving programs Experience in robotic systems: perception, localization, planning, control Knowledge of urban driving edge cases and sensor-heavy ML systems Exposure to automotive standards, safety, or validation workflows (e.g., ISO 26262 awareness) Experience operating ML platforms at enterprise or fleet scale 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: Private health care (Signal Iduna) and Life insurance for you and your beloved onesWell-Being Program that includes regular webinars, workshops, and networking eventsHybrid work (min. 47 days/yr of remote work, flexible working hours)Employee Pension Plan paid by the employer (you get + 3,5% on each gross salary)Access to sports groups and Multisport card 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.