DescriptionChange the world. Love your job.
In your first year with TI youll participate in our Career Accelerator Program (CAP) designed for professionals with advanced degrees. This program offers cutting-edge technical training and resources to fast-track your integration into TI and set you up for accelerated career growth. Our function-specific advanced training and high-impact projects will challenge you to solve complex problems through innovative hands-on experiences from day one.
About the job:
Design and build AI enabled solutions for discriminative and generative applications using a combination of classical and neural network (MLPs RNNs CNNs GNNs transformers) based machine learning algorithms. Put together efficient data pipelines develop agents using the latest LLMs or train new networks from scratch test with rigor and monitor deployments for accuracy and drift.
Work with partners across TI to address a wide variety of applications including design (software digital analog) manufacturing (process development fabrication testing) sales (pricing recommendations) planning and general productivity. Address problems at the intersection of math physics and engineering. Leverage human side information and physical constraints to improve AI model design and training. Deliver robust scalable performant and secure solutions.
Move comfortably between models which are human derived from observation and models which are learned from data via a common foundation of math (linear algebra calculus probability and optimization).
QualificationsMinimum Requirements:
- Masters and / or PhD in Electrical Engineering Computer Engineering Computer Science Physics Math or related technical field of study
- Cumulative 3.0 / 4.0 GPA or higher
Preferred Qualifications:
- AI / ML
- Development of novel neural network related algorithms and associated publication in top technical conferences
- Design training and use of the latest transformer based LLMs (reasoning agents)
- Design training and use of additional neural network types (MLPs RNNs CNNs GNNs)
- Design training and use of neural networks with physical constraints (e.g. PINNs)
- Traditional ML based techniques (clustering regression trees )
- AI / ML based approaches to language speech vision games time series and personalization related applications
- Programming
- Python programming and the PyTorch package
- C / C programming
- Math
- Dense linear algebra probability and calculus
- Optimization theory and algorithms
- Personal
- Strong technical leadership communication and interpersonal skills
- The ability to dream what could be and the drive to make the dream a reality
Required Experience:
IC
DescriptionChange the world. Love your job.In your first year with TI youll participate in our Career Accelerator Program (CAP) designed for professionals with advanced degrees. This program offers cutting-edge technical training and resources to fast-track your integration into TI and set you up fo...
DescriptionChange the world. Love your job.
In your first year with TI youll participate in our Career Accelerator Program (CAP) designed for professionals with advanced degrees. This program offers cutting-edge technical training and resources to fast-track your integration into TI and set you up for accelerated career growth. Our function-specific advanced training and high-impact projects will challenge you to solve complex problems through innovative hands-on experiences from day one.
About the job:
Design and build AI enabled solutions for discriminative and generative applications using a combination of classical and neural network (MLPs RNNs CNNs GNNs transformers) based machine learning algorithms. Put together efficient data pipelines develop agents using the latest LLMs or train new networks from scratch test with rigor and monitor deployments for accuracy and drift.
Work with partners across TI to address a wide variety of applications including design (software digital analog) manufacturing (process development fabrication testing) sales (pricing recommendations) planning and general productivity. Address problems at the intersection of math physics and engineering. Leverage human side information and physical constraints to improve AI model design and training. Deliver robust scalable performant and secure solutions.
Move comfortably between models which are human derived from observation and models which are learned from data via a common foundation of math (linear algebra calculus probability and optimization).
QualificationsMinimum Requirements:
- Masters and / or PhD in Electrical Engineering Computer Engineering Computer Science Physics Math or related technical field of study
- Cumulative 3.0 / 4.0 GPA or higher
Preferred Qualifications:
- AI / ML
- Development of novel neural network related algorithms and associated publication in top technical conferences
- Design training and use of the latest transformer based LLMs (reasoning agents)
- Design training and use of additional neural network types (MLPs RNNs CNNs GNNs)
- Design training and use of neural networks with physical constraints (e.g. PINNs)
- Traditional ML based techniques (clustering regression trees )
- AI / ML based approaches to language speech vision games time series and personalization related applications
- Programming
- Python programming and the PyTorch package
- C / C programming
- Math
- Dense linear algebra probability and calculus
- Optimization theory and algorithms
- Personal
- Strong technical leadership communication and interpersonal skills
- The ability to dream what could be and the drive to make the dream a reality
Required Experience:
IC
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