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Key skills for this role
We are seeking a highly skilled AI/ML + DevOps / MLOps Engineer to design, deploy, and manage scalable machine learning pipelines and cloud-native infrastructure. The role combines expertise in AI/ML workflows, DevOps practices, and cloud platforms to enable efficient model development, deployment, and lifecycle management in production environments.
We’re a global, multi-disciplinary team that’s putting the innovative power of technology to work and transforming tomorrow. At HARMAN Automotive, we give you the keys to fast-track your career.
Engineer audio systems and integrated technology platforms that augment the driving experience
Combine ingenuity, in-depth research, and a spirit of collaboration with design and engineering excellence
Advance in-vehicle infotainment, safety, efficiency, and enjoyment
We are seeking a highly skilled AI/ML + DevOps / MLOps Engineer to design, deploy, and manage scalable machine learning pipelines and cloud-native infrastructure. The role combines expertise in AI/ML workflows, DevOps practices, and cloud platforms to enable efficient model development, deployment, and lifecycle management in production environments.
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3–6 years of experience in: AI/ML Engineering DevOps / MLOps
AI/ML Engineering
DevOps / MLOps
Strong hands-on expertise in: CI/CD tools (GitLab CI, Jenkins, Argo CD) Cloud platforms (AWS / Azure) Kubernetes and container orchestration
CI/CD tools (GitLab CI, Jenkins, Argo CD)
Cloud platforms (AWS / Azure)
Kubernetes and container orchestration
Experience in Infrastructure as Code (Terraform)
Good understanding of: Machine Learning lifecycle Model deployment and monitoring Data pipelines and automation
Machine Learning lifecycle
Model deployment and monitoring
Data pipelines and automation
Strong programming/scripting skills in: Python
Python
Solid understanding of: Microservices architecture Distributed systems
Microservices architecture
Distributed systems
Experience working in Agile environments
Strong problem-solving and analytical skills
Experience with: ML frameworks (TensorFlow, PyTorch, Scikit-learn) MLOps tools (MLflow, Kubeflow, SageMaker)
ML frameworks (TensorFlow, PyTorch, Scikit-learn)
MLOps tools (MLflow, Kubeflow, SageMaker)
Knowledge of: Data engineering pipelines Streaming platforms (Kafka)
Data engineering pipelines
Streaming platforms (Kafka)
Experience with: Monitoring tools (Prometheus, Grafana) Logging systems
Monitoring tools (Prometheus, Grafana)
Logging systems
Exposure to automotive or embedded AI environments
Bachelor’s / Master’s degree in: Computer Science Data Science Electronics / IT
Computer Science
Data Science
Electronics / IT
Proven experience in: Cloud-native ML deployments CI/CD pipeline automation DevOps + AI/ML integration
Cloud-native ML deployments
CI/CD pipeline automation
DevOps + AI/ML integration
Verified company details for this employer are not available yet.
Full-time
Mid · 3+ years experience
Onsite
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