Job Description

Role: EMC AI/ML Engineer
Work Location: Cupertino, CA (Need candidates who can go for inperson interview)
Position Type: Full Time Permanent

The ES team will engage in cutting-edge projects focused on developing and implementing machine learning (ML) algorithms and models, with a strong emphasis on Generative AI. Responsibilities include data analysis, model training and evaluation, working with large datasets, and integrating generative models into real-world applications. AI/ML engineers collaborate with researchers, engineers, and program/ project managers to tackle innovative challenges and drive advancements in Generative AI.

Key Benefits
Various teams within EMC/PACE/PI can leverage Generative AI/ML to enhance productivity, automation, and innovation.
Implementation of state-of-the-art Generative AI/ML models to solve complex EMC problems.
Improved efficiency in EMC validation and testing through AI-driven approaches.

In Scope
Coordinate with teams on the validation and enhancement of Generative AI/ML models.
Collaborate with EMC and cross-functional teams to diagnose and resolve AI/ML-related software issues.
Develop and optimize generative AI/ML models to support EMC testing and automation.
Prepare and execute EMC test plans for AI/ML applications.
Maintain and optimize the performance of existing and future Generative AI/ML models.
Develop, customize, and maintain scripts to be used during EMC testing and ML model deployment.

Success Criteria/Definition of Done
Completion of EMC validation for all requests related to Generative AI applications.
Successful integration of Generative AI models into supported projects.
Improved performance and efficiency in EMC test automation using AI/ML.
Delivery of comprehensive reports and analyses on model performance and validation.

Technical Requirements
Expertise in C++ and Python programming.
Strong background in building, adapting, and fine-tuning Generative AI models (e.g., GANs, VAEs, Diffusion Models).
Practical experience with deep learning frameworks such as TensorFlow, PyTorch, CoreFlow, Sklearn, etc.
Familiarity with multimodal LLMs, large-scale model training, and optimization techniques.
Experience in integrating Generative AI/ML research prototypes into production applications.
Strong analytical and problem-solving skills.
Excellent written and verbal communication skills.
Highly motivated with excellent organizational skills.
5+ years of relevant experience in AI/ML Software Development or related fields.

Expectations by Phase
1. Discovery/Assignment Prep
Understanding project goals and AI integration needs.
Identifying key AI models and strategies.
2. Build Planning and Script Development
Designing AI pipelines and automation scripts.

3. Data Collection & Model Training
Gathering large-scale datasets for Generative AI training.
Implementing and fine-tuning Generative AI models.
4. Data Analysis & Model Evaluation
Evaluating AI model performance and effectiveness.
Running comparative analyses for improvement.
5. Report Generation & Review
Preparing comprehensive reports on AI model validation.
Collaborating with engineers for optimization.
6. Pipeline Maintenance & Continuous Improvement
Ensuring robustness and scalability of AI solutions.
Refining AI models based on test results and feedback.

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