Skyworks is seeking a technical AI/ML engineering leader to solve engineering problems in the semiconductor space by bringing AI solutions to production.
Requirements
- Hands-on experience with neural networks, deep learning architectures such as CNNs, RNNs, Transformers and Generative AI.
- Exposure to MLOps practices: monitoring, scaling, and automating ML workflows
- Experience with big data platforms: Databricks, Hadoop, Spark, Dataflow, etc or comparable products
- Proficiency in programming languages such as Python (preferred), Java, Csharp, or C++ 7 years experience
- Deep understanding of machine learning frameworks: PyTorch, scikit-learn, Keras, etc.
- Experience with data manipulation tools: NumPy, SQL, Pandas
- Familiarity with cloud and Data computing platforms: Azure, Azure DevOps, DataBricks or comparable platforms like GCP, BIgQuery
Responsibilities
- Design and develop ML models for high impact engineering solutions.
- Build, train, and optimize machine learning and deep learning models to solve complex problems using natural language processing, computer vision, and predictive analytics.
- Design, implement, and maintain scalable and reliable machine learning infrastructure and pipelines.
- Establish best practices for model development, deployment, monitoring, and lifecycle management.
- Collaborate with data scientists, product managers, and software engineers to deliver AI solutions aligned with business objectives.
- Manage and optimize cloud and on-premises resources for efficient training, serving, and experimentation of machine learning models.
- Automate processes for continuous integration and deployment (CI/CD) of machine learning models.
Other
- Education: Bachelor with 12+ years of professional experience in machine learning, artificial intelligence, or related fields. Preferably with a Master’s degree or A PhD or relevant research experience in Computer Science, Engineering, Mathematics, Statistics, or a related field.
- Experience managing and guiding AI/ML engineering and operations teams.
- Ensure compliance with data privacy, security, and ethical standards in all AI/ML operations.
- Develop documentation, training programs, and onboarding resources for new team members and stakeholders.
- Stay current with industry trends, research, and emerging technologies, integrating relevant advances into operational practices.
