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.