Renesas Design Vietnam

Tóm tắt công việc

About this role

As an MLOps Engineer, you will automate and streamline the process of integrating and maintaining machine learning models for both traditional and generative AI.

About our team

Our global AI, Data & Analytics Division at Renesas is experiencing an increasing demand for AI and Generative AI (LLM) based solutions. Working closely with our business partners, we deliver AI solutions to help drive value for Renesas at a global enterprise scale. We are seeking passionate candidates that will thrive as part of a global team of technologists that love empowering customers, collaborating with teammates, and using the latest AI and Data technologies.

Responsibilities

• Optimize and monitor the performance, reliability, and security of AI/ML systems.
• Applying best practices and standards for data quality, code quality, version control, CI/CD, and documentation.
• Developing, testing, deploying, and monitoring scalable and reliable machine learning pipelines using Databricks.
• Troubleshooting and resolving issues related to data, model, and infrastructure performance and availability.
• Researching and evaluating new technologies and frameworks for improving the efficiency and effectiveness of machine learning workflows.

Must Have

• Bachelor's degree or higher in computer science, mathematics, or a related field.
• Experience with DevOps, MLOps, or LLMOps tools and methodologies, such as Git, Docker, Kubernetes, Jenkins, Airflow, Kubeflow, etc.
• Proficiency in Python, SQL, and at least one of the following frameworks and libraries: TensorFlow/PyTorch, Scikit-learn, etc.
• Familiarity with Databricks products and services.
• Have working knowledge of CI/CD.
• Strong communication, documentation, and white-boarding skills.
• Strong interest in collaboration, learning, and driving value through ML.

Strongly Preferred

• Databricks certifications.
• Experience with Databricks, Mlflow, Spark, Delta Lake, and other components of the Databricks Unified Data Analytics Platform.
• Working knowledge of at least one major cloud ecosystem (AWS, Azure, or GCP). Azure is preferred.
• Knowledge in LLM actual use cases.
• Experience working with a geographically distributed and cross-functional team including systems integrators and third-party companies.