Senior Staff Engineer - AI Cloud Data Platform Technical Product Manager at Infineon Technologies AG Australia

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

12 Feb, 26

Salary

0.0

Posted On

14 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Science, Technical Product Management, Cloud Data Platforms, MLOps, Data Governance, Analytics, Agile Development, Python, SQL, Machine Learning, Deep Learning, Data Analytics, Business Intelligence, DevOps, Large Language Models, Workflow Orchestration

Industry

Semiconductor Manufacturing

Description

Design and develop concepts for scalable data platforms and products, encompassing data acquisition, pipelines, labeling, analytics, and AI deployment. Develop detailed product requirements and technical specifications for data infrastructure and services. Collaborate with data engineering, data science, and MLOps teams to design and evolve our data platform architecture on the cloud. Ensure platform and product designs meet both technical and business requirements, focusing on scalability, reliability, and data governance. Collaborate with engineering teams through agile methodologies to develop, deploy, and iterate on data products. Ensure all data products meet the highest quality and reliability standards, implementing robust data governance and quality controls. Collaborate with engineering teams to build and optimize robust data pipelines and MLOps workflows to support the entire machine learning lifecycle. Provide technical guidance on creating insightful dashboards and optimizing data availability lead times for various stakeholders. Work with teams to integrate workflow orchestration and improve efficiency and cost at each step of the data lifecycle. Collaborate with engineering teams to design and develop Large Language Model (LLM) enabled platform capabilities and applications. Provide technical guidance on integrating LLM agents to enhance product features, such as enabling natural language interaction with our data platforms. Collaborate with data science teams to implement and scale deep learning models that enable accurate and efficient data analysis. Provide technical guidance on model deployment, monitoring, and integration with the core data platform. Develop and maintain the technical roadmap for the AI data platform. Collaborate with engineering and business units to align the roadmap with company-wide objectives. 6-8 years of experience in data engineering, data science, or technical product management for data-intensive products. A Bachelor's or Master's degree in Computer Science, Electrical/Electronics Engineering, or a related field. Excellent problem-solving skills and meticulous attention to detail. Extensive experience with cloud data platforms such as GCP or AWS. Strong technical knowledge of data engineering, MLOps, data governance, and analytics. Proven experience with technical product management and data product design. Experience with agile development methodologies and leading cross-functional teams. Proficiency with data processing technologies and languages like Python and SQL. Experience with data analytics, business intelligence, and machine learning. Certifications in cloud or AI technologies (e.g., Microsoft Azure Fundamentals, AWS Certified Data Engineer). Experience with DevOps tools and practices. We are on a journey to create the best Infineon for everyone. This means we embrace diversity and inclusion and welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect and tolerance and are committed to give all applicants and employees equal opportunities. We base our recruiting decisions on the applicant´s experience and skills. Please let your recruiter know if they need to pay special attention to something in order to enable your participation in the interview process. Click here for more information about Diversity & Inclusion at Infineon.

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Responsibilities

Design and develop scalable data platforms and products, ensuring they meet technical and business requirements. Collaborate with various teams to optimize data pipelines and MLOps workflows, while providing technical guidance on model deployment and integration.