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Automated Reasoning Jobs in Texas (NOW HIRING)

Photon

Product Manager - Dallas, TX

Dallas, TX · On-site

... of reasoning, planning, and executing tasks. You will bridge the gap between complex AI research ... Identify use cases where AI agents can provide the most ROI-such as automated research, proactive ...

Photon

Product Manager - Dallas, TX

Dallas, TX · On-site

... of reasoning, planning, and executing tasks. You will bridge the gap between complex AI research ... Identify use cases where AI agents can provide the most ROI-such as automated research, proactive ...

Deloitte

Agentic AI Engineer - Healthcare AI

Austin, TX · On-site

Build the reasoning behind regulated decisions - policy- and criteria-grounded outputs, structured ... metrics, automated checks, and human review. Engineer healthcare-grade safety - deployment eval ...

Deloitte

Agentic AI Engineer - Healthcare AI

Dallas, TX · On-site

Build the reasoning behind regulated decisions - policy- and criteria-grounded outputs, structured ... metrics, automated checks, and human review. Engineer healthcare-grade safety - deployment eval ...

Federal Express Corporation

AI Engineer III

Plano, TX · On-site

Establish automated evaluation suites using agents-cli eval, Vertex AI GenAI Evaluation Service , and continuous regression testing for reasoning, tool fidelity, and context relevance. * Implement ...

Baylor Genetics

Automation Engineer II

Houston, TX · On-site

Develop, test, implement, and optimize automated laboratory assays and workflows to improve ... Mechanical aptitude and understanding of laboratory automation systems; strong spatial reasoning ...

Baylor Genetics

Automation Engineer II

Houston, TX · On-site

Develop, test, implement, and optimize automated laboratory assays and workflows to improve ... Mechanical aptitude and understanding of laboratory automation systems; strong spatial reasoning ...

Aalo Atomics

Senior Controls Development Engineer

Austin, TX · On-site

$96K - $126K/yr

Design and architect PLC/HMI-based control systems for automated and semi-automated manufacturing ... Strong communication skills to convey technical reasoning and mission-critical messaging clearly ...

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Automated Reasoning information

What is automated reasoning?

Automated reasoning is a field of computer science and mathematical logic dedicated to understanding how reasoning can be automated using computers. It involves developing algorithms and software that allow computers to prove theorems, verify software and hardware systems, and solve logical problems. Automated reasoning is used in areas such as formal verification, artificial intelligence, and knowledge representation, helping to ensure systems behave as intended and are free of certain types of errors.

What are the key skills and qualifications needed to thrive as an automated reasoning engineer?

To thrive as an Automated Reasoning Engineer, you need a strong background in computer science, logic, and formal verification, often supported by an advanced degree in a related field. Familiarity with formal methods tools (such as SMT solvers, model checkers), programming languages like Python, C++, or OCaml, and experience with verification frameworks are typically important. Analytical thinking, problem-solving, and effective communication skills help engineers tackle complex proofs and collaborate with interdisciplinary teams. These skills are crucial for ensuring the reliability and correctness of software and hardware systems in safety-critical environments.

What are some common challenges faced by professionals working in automated reasoning roles?

Professionals in Automated Reasoning often encounter challenges such as handling highly complex logical problems, ensuring the scalability of reasoning algorithms, and integrating automated reasoning tools with existing systems. Collaborating with interdisciplinary teams—including software engineers, data scientists, and domain experts—can present communication hurdles, as explaining formal logic concepts to non-experts is sometimes necessary. Additionally, staying up-to-date with the latest research and advancements in theorem proving and formal verification is crucial for continued success in this rapidly evolving field.

What are popular job titles related to Automated Reasoning jobs in Texas?

For Automated Reasoning jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Automated Reasoning jobs in Texas look for?

The top searched job categories for Automated Reasoning jobs in Texas are:

What cities in Texas are hiring for Automated Reasoning jobs?

Cities in Texas with the most Automated Reasoning job openings:

Automated Reasoning jobs near you
Infographic showing various Automated Reasoning job openings in Texas as of August 2026, with employment types broken down into 85% Full Time, 8% Part Time, 5% Contract, and 2% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Engineering Manager, AI Compiler Analysis

Austin, TX

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidiaexternal

Full-time

Re-posted 12 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

Job description

NVIDIA's invention of the GPU transformed computer graphics, parallel computing, and modern AI. Today, NVIDIA high-performance processing platforms power breakthroughs across generative AI, autonomous systems, scientific computing, robotics, and high-performance data centers.

NVIDIA's compiler technologies are key enablers of AI at scale, turning rapidly evolving deep learning models into highly optimized GPU programs for training and inference. As AI models, GPU architectures, and compiler systems become more sophisticated, AI compiler quality has become a deep technical challenge at the intersection of compilers, machine learning frameworks, numerical computing, formal reasoning, and large-scale systems engineering. To address these complex challenges, we are seeking an Engineering Manager to spearhead our strategy for verifying AI compilers built for next-generation deep learning workloads. This is a hands-on compiler engineering leadership role for someone who understands where compiler quality can regress in modern AI compiler stacks.

What You'll Be Doing:

  • Lead, mentor, and grow a highly technical team responsible for AI compiler verification.

  • Own the verification of next-generation AI workloads, including LLMs and agentic AI systems, across the full spectrum of the AI compiler stack and execution pipeline.

  • Define formal-verification requirements for AI compiler transformations and generated GPU programs, including formal specifications, tensor/operator semantics, semantic preservation, code equivalence, numerical behavior, and properties stressed by AI-generated or adversarial workloads.

  • Drive the use of AI-assisted and compiler-aware verification techniques, including adversarial workload generation, differential testing, symbolic reasoning, formal methods, fuzzing, static analysis, and automated debugging.

  • Partner closely with AI compiler development, CUDA software, ML framework, runtime, product, and AI software teams to build scalable verification infrastructure, improve engineering velocity, and increase production confidence.

What We Need To See:

  • BS, MS, or PhD in Computer Science, Computer Engineering, or a related field, or equivalent experience.

  • 10+ overall years of total relevant software engineering experience, including at least 3 years experience leading engineering teams or major technical initiatives.

  • Experience with AI compiler or framework technologies such as MLIR, TensorRT, XLA, Triton, PyTorch, or JAX.

  • Fluency with AI workload and ML framework concepts, including computation graphs, tensor operations, model execution, and training or inference workflows.

  • Strong people management skills, including hiring, mentoring, performance management, and team development.

Ways To Stand Out From The Crowd:

  • Hands-on with deep learning compiler internals, including compiler IRs, optimization and lowering pipelines, code generation, runtime integration, or production compiler infrastructure.

  • Experience verifying performance-sensitive compiler behavior and root-causing subtle regressions in production AI/ML systems using computational methods, fuzzing, code inspection, or automated debugging.

  • Background in formal verification or programming languages, with familiarity in formal specifications, theorem proving, Lean, SMT/SAT solvers, or symbolic reasoning.

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD for Level 2, and 200,000 USD - 322,000 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 3, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

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