Early Career - AI for Analog Design Engineer at Texas Instruments
Dallas, TX
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Jul 6, 2026
Dallas, TX
Jul 20, 2026
What this job asks for AI summary
This role sits within Texas Instruments' IT organization and focuses on building AI-powered tools to speed up analog circuit design, sizing, and layout for internal IC development teams. The work spans classical and neural-network approaches (including MLPs, RNNs, CNNs, GNNs, and transformers), LLM-based agents, data pipelines, and model monitoring in production. It suits someone with combined expertise in machine learning and analog circuit design.
Mid level · Dallas-Fort Worth-Arlington, TX · Full-time
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 370 people in the Dallas-Fort Worth-Arlington, TX area plausibly meet what this posting asks for (data scientists). range 280–480
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $130,559 (middle half $92,500–$149,977).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (3)
The posting blends data science (ML model training, neural networks, generative AI) with software engineering (building production-ready solutions, data pipelines, agents), making the SOC classification genuinely ambiguous. The primary emphasis on model development, training, and evaluation tips it toward Data Scientists (15-2051), with Software Developers (15-1252) as a close runner-up.
No explicit requirements section is present — the entire posting is written as a narrative of responsibilities. Skills have been classified as required when they are central, repeated duties (ML, LLMs, data pipelines, neural networks) and preferred for the specific network architectures (MLPs, RNNs, CNNs, GNNs, transformers) listed as examples of a broader capability.
No compensation, experience-year minimums, degree requirements, or remote/hybrid details are stated in the posting.
Read the full posting
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