Early Career - AI Solutions Engineer

Texas Instruments • Dallas, TX

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About The Position

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).

Requirements

• Master's 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
• Python programming and the PyTorch package
• C / C++ programming
• Dense linear algebra, probability, and calculus
• Optimization theory and algorithms

Nice To Haves

• 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
• Strong technical leadership, communication and interpersonal skills
• The ability to dream what could be and the drive to make the dream a reality

Responsibilities

• Design and build AI enabled solutions for discriminative and generative applications using a combination of classical and neural network 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, manufacturing, sales, 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Number of Employees: 5,001-10,000 employees