We are seeking a motivated and hands‐on Data Scientist to join our team and help develop data‐driven and AI‐enabled solutions in the semiconductor domain.
This role focuses on building practical machine learning applications from proof‐of‐concept through production, while collaborating closely with cross‐functional engineering teams.
The Role
Our team develops analytical and machine learning solutions that support engineering, testing, and performance optimization efforts across multiple domains.
We emphasize rapid prototyping, iterative development, and close collaboration with stakeholders to ensure high‐impact deliverables.
Responsibilities
Develop, train, validate, and deploy machine learning models for real‐world applications
Perform data collection, cleaning, transformation, and feature engineering on structured and unstructured datasets
Build and maintain scalable data pipelines and ETL processes using Python, SQL, and related tools
Conduct model selection, evaluation, and tuning, ensuring robustness and avoiding overfitting
Collaborate with cross‐functional teams to move prototypes into production environments
Contribute to the design and implementation of end‐to‐end ML workflows (MLOps lifecycle)
Develop proof‐of‐concept solutions and iterate toward production‐ready systems
Document methodologies, data sources, models, and system behavior




Participate in code reviews and promote best practices in development and deployment
Desired Experience And Skills
Experience with LLM‐based solutions such as RAG (Retrieval‐Augmented Generation), LangChain, or agent‐based systems
Familiarity with containerization technologies such as Docker
Exposure to full‐stack development concepts (JavaScript, Node.js) for integrating data products into applications
Experience working with experimentation frameworks and prototyping workflows
Required Experience And Skills
Strong experience with Python for data science and machine learning
Proficiency in data manipulation and analysis using Pandas, NumPy
Solid SQL skills for data extraction and transformation
Experience building and evaluating ML models using frameworks such as scikit‐learn, PyTorch, or Keras
Understanding of feature engineering, model validation techniques, and performance metrics
Experience building data pipelines and ETL processes
Ability to translate business or engineering problems into data science solutions
What We Value
Passion for building practical, deployable AI solutions
Ownership mindset from prototype to production
Curiosity and willingness to learn new tools and techniques
Collaboration and transparency across teams
Skyworks is proud to be an equal opportunity employer supporting diversity in the workplace.
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📌 Data Scientist (Mexicali)
🏢 Skyworks Solutions
📍 Mexicali