Advanced Engineer - AI/ML with Devops(GCP,AWS)

Job Summary

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

About the Role

We are looking for a highly motivated AI / ML with Devops (GCP,AWS) with 6 to 9 years of experience, who is passionate about building intelligent systems and automating end-to-end ML workflows. The ideal candidate will have a strong foundation in Machine Learning, Python automation, DevOps practices, and cloud-based deployments, working closely with cross-functional teams to deliver scalable, reliable AI solutions.

What You Will Do

• Design, develop, train, and deploy Machine Learning and AI models for real-world applications.
• Build end-to-end ML pipelines, including data preprocessing, model training, validation, deployment, and monitoring.
• Develop Python-based automation for test suites, model validation, and workflow orchestration.
• Integrate ML pipelines seamlessly into CI/CD pipelines for continuous testing and deployment.
• Ensure a smooth and consistent build environment using CMake and Bazel.
• Collaborate with DevOps teams to enable MLOps best practices, including model versioning and reproducibility.
• Deploy, monitor, and optimize ML workloads in AWS environments.
• Actively contribute to code reviews, documentation, and technical discussions.
• Troubleshoot and resolve build, deployment, and performance issues across environments.

What You Need to Be Successful

• 6 to 9 years of hands-on experience in AI / Machine Learning development.
• Strong proficiency in Python, especially for automation, ML model development, and testing.
• Extensive hands-on experience in automating test suites and processes using Python.
• Solid experience integrating ML and automation workflows into CI/CD pipelines.
• Hands-on experience with version control systems such as Git, GitLab, and GitHub.
• Strong understanding of DevOps practices, including build, release, and deployment automation.
• Experience working with AWS cloud services for ML model deployment and infrastructure.
• Practical experience with CMake and Bazel for managing and maintaining stable build environments.
• Good problem-solving skills with a strong attention to detail.

Bonus Points If You Have

• Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Airflow, etc.).
• Exposure to containerization and orchestration technologies like Docker and Kubernetes.
• Experience with data processing frameworks (Pandas, NumPy, Spark, etc.).
• Knowledge of REST APIs / microservices for ML model serving.
• Familiarity with monitoring and logging tools in cloud environments.
• Prior experience in agile / scrum development teams.

What Makes You Eligible

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related fields.
• Strong understanding of ML fundamentals, algorithms, and model lifecycle management.
• Excellent communication and collaboration skills.
• Ability to work independently while contributing effectively to cross-functional teams.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.