Software Engineer - ML Ops DevOps

About the 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.

Responsibilities

• Design and implement end-to-end MLOps pipelines for model development, training, deployment, and monitoring
• Build and manage CI/CD pipelines using: GitLab CI
• Jenkins
• Argo CD
• Deploy and manage ML workloads on cloud platforms: AWS
• Azure
• Develop and maintain containerized applications using: Docker
• Kubernetes
• Implement infrastructure automation using Terraform (IaC)
• Enable scalable and reliable ML model deployment using: Kubernetes orchestration
• Microservices architecture
• Monitor ML models in production for: Performance
• Drift
• Reliability
• Optimize deployment workflows and reduce latency for ML inference
• Collaborate with: Data Scientists
• Software Engineers
• DevOps teams
• to integrate ML models into production systems
• Build automated pipelines for: Data ingestion
• Model training & validation
• Versioning and deployment
• Ensure adherence to best practices in DevOps, security, and cloud governance
• What You Need to Be Successful
• 3-6 years of experience in: 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
• Experience in Infrastructure as Code (Terraform)
• Good understanding of: Machine Learning lifecycle
• Model deployment and monitoring
• Data pipelines and automation
• Strong programming/scripting skills in: Python
• Solid understanding of: Microservices architecture
• Distributed systems
• Experience working in Agile environments
• Strong problem-solving and analytical skills
• Bonus Points If You Have
• Experience with: ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• MLOps tools (MLflow, Kubeflow, SageMaker)
• Knowledge of: Data engineering pipelines
• Streaming platforms (Kafka)
• Experience with: Monitoring tools (Prometheus, Grafana)
• Logging systems
• Exposure to automotive or embedded AI environments
• What Makes You Eligible
• Bachelor's / Master's degree in: Computer Science
• Data Science
• Electronics / IT
• Proven experience in: Cloud-native ML deployments
• CI/CD pipeline automation
• DevOps + AI/ML integration

Benefits

Additional Information

HARMAN's engineers and designers are creative, purposeful and agile. As part of this team, you'll combine your technical expertise with innovative ideas to help drive cutting-edge solutions in the car, enterprise and connected ecosystem. Every day, you will push the boundaries of creative design, and HARMAN is committed to providing you with the opportunities, innovative technologies and resources to build a successful career. A Career at HARMAN As a technology leader that is rapidly on the move, HARMAN is filled with people who are focused on making life better. Innovation, inclusivity and teamwork are a part of our DNA. When you add that to the challenges we take on and solve together, you'll discover that at HARMAN you can grow, make a difference and be proud of the work you do everyday. Introduction: A Career at HARMAN Automotive 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

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