About the role
If you are looking for a challenging and exciting career in the world of technology, then look no further. Skyworks is an innovator of high performance analog semiconductors whose solutions are powering the wireless networking revolution. At Skyworks, you will find a fast-paced environment with a strong focus on global collaboration, minimal layers of management and the freedom to make meaningful contributions in a setting that encourages creativity and out-of-the-box thinking. We are excited about the opportunity to work with you and glad you want to be part of a team of talented individuals who together can change the way the world communicates.
Requisition ID: 74860
Job Responsibilities
Collaborate with stakeholders: Engage with business stakeholders, data engineers, software engineers, and other teams to understand their requirements and align data initiatives with overall business goals. ·
Integration and interoperability: Work on solutions that seamlessly integrate with existing enterprise systems, databases, and APIs. Collaborate with internal and external partners to enable smooth data flow and interoperability across systems, ensuring consistent and accurate inputs for machine learning models.
Risk assessment and mitigation: Identify potential risks and challenges related to machine learning operations, such as data privacy, security vulnerabilities, or ethical considerations. Propose and implement mitigation strategies to ensure compliance, data integrity, and model robustness.
Continuous improvement: Continuously evaluate and optimize the machine learning operations infrastructure and processes to improve efficiency, reliability, and scalability. Stay informed about advancements in machine learning operations and recommend new tools, frameworks, or methodologies that can enhance the organization's capabilities
Data operations: Build and support data flows for moving or sourcing data sets for training and inferencing. This includes understanding the data requirements, identifying the best methods for data transfer, and implementing the data pipelines.
RAG applications: Pioneer the creation of RAG applications by collecting the data needed and implementing solutions using LLM's, vector databases, and database indexing
Job Requirements
Enrolled in a Bachelor's or Graduate level program in Computer Science, Artificial Intelligence, Information Technology or related field
Strong knowledge of BigData concepts, frameworks and technologies, such as Python, NumPy, Pandas, Pyspark,Databrciks,SQL
Experience with DevOps tools and practices, such as CI/CD, Docker, Kubernetes.
Experience with SQL and NoSQL database e.g. MSSQL and PostgreSQL
Demonstrated expertise in architecting scalable infrastructure, including data pipelines, storage systems.
Excellent communication and collaboration skills, with the ability to effectively engage with stakeholders at various levels of the organization
Ability to multitask and manage multiple activities simultaneously · Ability to use a wide degree of creativity and latitude to think differently, challenge conventional wisdom, and drive new best practices
Ability to work effectively with international teams
