Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 brand, mid-level (≈4yr) ML role in Bengaluru with broad requirements drives high competition.
Core ML/MLOps skills transferable, but automotive and embedded deployment preference raises domain sensitivity.
Explicit ~4 years and required ML/MLOps, data pipeline, and deployment skills imply medium strictness.
Design, develop, and deploy AI/ML models and data pipelines for automotive applications including driver monitoring, predictive analytics, and connected vehicles.
Implement DevOps/MLOps practices such as CI/CD, containerization, and automated testing to support AI/ML solution deployment and scalability.
Enhance developer productivity by integrating AI-assisted tools for code review, generation, documentation, and workflow automation.
Around 4 years of experience in AI/ML engineering, preferably in the automotive domain.
Strong programming skills in Python and working knowledge of machine learning and deep learning concepts.
Experience with data pipelines (e.g., Spark, Airflow, Kafka) and DevOps/MLOps tools (Docker, Kubernetes, CI/CD, Git).
Bachelor's or Master's degree in Computer Science, Electronics, Data Science, Artificial Intelligence, Automotive Engineering, or related field.
Experienced operating at the intersection of AI/ML engineering, data engineering, and DevOps, with the ability to independently own technical tasks.
Familiar with automotive domains such as ADAS, autonomous driving, or vehicle diagnostics to effectively tailor AI/ML solutions.
Skilled in adopting developer productivity tools and workflows leveraging AI to improve engineering efficiency and software quality.