AI/ML Engineer

As an AI/ML Engineer specializing in automotive data, DevOps, and developer productivity, you will play a key role in designing, developing, deploying, and maintaining AI/ML solutions for connected, embedded, or vehicle-related applications. Your focus will be on enhancing engineering efficiency, code quality, and automation using machine learning, data pipelines, and DevOps/MLOps practices. Your responsibilities will include: - Designing, developing, and optimizing AI/ML models for automotive use cases such as driver monitoring, predictive analytics, perception, diagnostics, or connected vehicle applications. - Building and maintaining data pipelines for data collection, preprocessing, transformation, validation, and feature engineering from structured and unstructured sources. - Working on end-to-end model lifecycle activities including training, evaluation, deployment, versioning, and performance monitoring. - Collaborating with software, data, validation, and platform teams to integrate AI/ML components into production systems. - Supporting deployment of AI/ML workloads using DevOps/MLOps practices, including CI/CD, containerization, automated testing, and infrastructure management. - Developing and maintaining scripts, APIs, and services for scalable model serving and batch/stream processing. - Contributing to developer productivity initiatives by leveraging AI tools for code review, code generation, documentation, test-case generation, defect analysis, and workflow automation. - Evaluating and integrating AI-assisted engineering tools to improve software development speed, code quality, and release efficiency. - Ensuring data quality, reproducibility, and traceability across datasets, code, and model artifacts. - Participating in troubleshooting, root-cause analysis, and continuous improvement of deployed AI/ML solutions. - Contributing to technical documentation, code reviews, and process standardization. Required Skills and Experience: - Around 4 years of experience in AI/ML engineering, preferably in the automotive domain. - Strong programming skills in Python. - Good understanding of machine learning and deep learning concepts. - Hands-on experience in building and maintaining data pipelines using tools/frameworks such as Spark, Airflow, Kafka, or similar. - Exposure to DevOps/MLOps practices, including Docker, Kubernetes, CI/CD pipelines, Git, and cloud/on-prem deployment workflows. - Experience with data preprocessing, feature engineering, model evaluation, and debugging. - Familiarity with APIs, microservices, and deployment of AI/ML solutions into production environments. - Good understanding of software engineering best practices, version control, testing, and documentation. Competencies Required: - Strong problem-solving and analytical skills. - Ability to work across AI/ML, data engineering, and DevOps domains. - Good collaboration skills to work with cross-functional engineering teams. - Strong ownership and ability to independently drive technical tasks. - Structured communication and documentation skills. - Ability to learn and adapt to new tools, frameworks, and engineering methods. Preferred Skills: - Experience in automotive domains such as ADAS, autonomous driving, driver monitoring, cockpit AI, vehicle diagnostics, or connected vehicle systems. - Exposure to frameworks such as PyTorch, TensorFlow, ONNX, or OpenCV. - Knowledge of MLOps tools like MLflow, Databricks, or model registry solutions. - Understanding of embedded or edge AI deployment is an added advantage. - Familiarity with cloud platforms such as AWS, Azure, or GCP. - Experience working in Agile teams and cross-functional product environments. - Exposure to developer productivity tools such as Claude, GitHub Copilot, Codeium, Cursor, AI PR reviewers, or similar platforms. Education: - Bachelors or Masters degree in Computer Science, Electronics, Data Science, Artificial Intelligence, Automotive Engineering, or related field. Please share your profiles to careers.swxindia@stellantis.com with below details: Total yrs. of exp: CCTC: ECTC: NP: (Note: Any additional details of the company were not included in the provided job description.) As an AI/ML Engineer specializing in automotive data, DevOps, and developer productivity, you will play a key role in designing, developing, deploying, and maintaining AI/ML solutions for connected, embedded, or vehicle-related applications. Your focus will be on enhancing engineering efficiency, code quality, and automation using machine learning, data pipelines, and DevOps/MLOps practices. Your responsibilities will include: - Designing, developing, and optimizing AI/ML models for automotive use cases such as driver monitoring, predictive analytics, perception, diagnostics, or connected vehicle applications. - Building and maintaining data pipelines for data collection, preprocessing, transformation, validation, and feature engineering from structured and unstructured sou