Top 10 Companies Hiring AI Engineers in Plano, TX in 2026

Table of Contents

• Your Menu for an AI Career in Plano
• FedEx Services
• NTT DATA
• PepsiCo
• Ericsson
• Texas Instruments
• Intuit
• Amazon
• JPMorgan Chase & Co.
• Capital One
• Toyota Motor North America
• Finding Your Perfect Fit
• Frequently Asked Questions

FedEx Services

At FedEx's massive Plano-area technology center, AI engineers tackle one of the planet's most complex optimization problems: orchestrating the movement of millions of packages daily. The company is undergoing a radical shift from a "shipping company with tech" to a "tech-first logistics" enterprise, where machine learning models directly control the efficiency of a global physical network.

The work centers on prediction and real-time reaction. Teams build systems for dynamic route optimization that respond to traffic, weather, and fluctuating demand, and develop computer vision for automated package handling. The stack is built for massive datasets, leveraging Python, Spark, and cloud-native ML platforms. As the company transforms, roles like AI/ML Engineer are in high demand across the DFW region, with senior positions at FedEx commanding salaries in the range of $160k to $195k.

The interview process reflects the applied nature of the work, typically involving a technical screen followed by a panel interview that focuses on problem-solving with real logistical datasets. Candidates report on sites like Glassdoor that such interviews test the ability to translate operational chaos into a clean, solvable ML problem.

Your impact here is uniquely tangible. A model's performance isn't just an abstract F1 score; it's measured by whether a critical medical shipment or a small business's crucial order arrives on time. You're solving the "last-mile" and every-mile-before-it challenge at a scale few other companies can offer.

NTT DATA

With its North American headquarters in Plano, NTT DATA operates as a strategic AI consultancy and implementation partner for Fortune 500 clients. This role is less about building a single product and more about being a versatile problem-solver across industries, offering what one engineer described on Glassdoor as a "consultancy playground" for AI talent.

The work is defined by its variety. You might architect a Generative AI agent for a pharmaceutical client one month and build a digital twin for a smart factory the next. This demands fluency in multi-cloud environments (AWS, Azure, GCP), Python, and the latest GenAI tools. Salaries reflect this broad expertise, with Machine Learning Engineers earning $115k to $145k and senior architects reaching up to $210k, according to salary data on Indeed.

The interview process typically involves an aptitude test followed by multiple technical rounds that deeply dissect your past project architecture and problem-solving approach. It's designed to assess how you think across domains.

This is the ideal role for engineers who are as fascinated by business transformation as they are by model architecture. Your project portfolio could quickly span:

• Healthcare diagnostics and drug discovery acceleration
• Retail supply chain and personalized recommendation systems
• Industrial IoT and predictive maintenance platforms

You gain exposure to a vast array of business challenges and datasets, all while helping define what enterprise AI looks like across the corporate landscape.

PepsiCo

PepsiCo's Plano-based Global Data & AI team represents a standout model of a mature, high-impact AI operation within a non-tech corporation. The mission is deceptively simple yet incredibly complex: use artificial intelligence to ensure the right bag of chips or bottle of soda is in the right place at the right time, optimizing a supply chain that stretches from farms to supermarket shelves.

The projects are intensely applied, directly tied to core business metrics like sales and efficiency. Engineers build forecasting models that predict regional snack cravings, implement computer vision for quality control on fast-moving production lines, and develop optimization algorithms for fleet routing. The stack is modern and cloud-centric, utilizing Python, PyTorch, and platforms like Azure and Databricks. Reflecting the value of this work, AI Engineer salaries at PepsiCo in Plano show a broad range from $106k to $178k based on experience and impact.

This work places you at the forefront of AI's integration into physical industry. As one industry expert noted about the manufacturing sector's transformation, "The humans will be able to use AI to do their jobs more effectively and more productively, and their value as a result will be even higher". The interview process mirrors this practical focus, emphasizing applied ML through case studies that ask candidates to solve tangible logistical or retail challenges.

You are tackling the "final frontier" of AI: the physical world. The complexity of moving billions of physical goods rivals any tech firm's challenges, but the domain - global food and beverage - is universally relatable. It's a chance to drive digital transformation within a beloved, century-old brand, where your models directly influence what happens in factories, warehouses, and stores.

Ericsson

At Ericsson's Plano office, AI engineers work on the fundamental infrastructure of modern connectivity. As a global leader in 5G and a pioneer in 6G research, the company uses artificial intelligence to manage and optimize the world's telecommunications networks - essentially building the intelligent nervous system of the internet itself.

The core mission is creating self-healing, predictive networks. Projects include developing models for real-time traffic forecasting, using anomaly detection to predict and prevent outages in thousands of cellular sites, and driving automation for radio frequency management. The tech stack emphasizes reliability at scale, built on Python, R, and cloud-native ML pipelines deployed via Kubernetes. Reflecting the specialized nature of this work, a Machine Learning Engineer can expect a salary range of $110k to $145k, with senior roles reaching $200k.

The interview process, as detailed by candidates on Glassdoor, often begins with an aptitude test, followed by technical assessments focused on ML fundamentals and behavioral rounds with hiring managers. It's designed to find engineers who can handle the immense responsibility of maintaining global systems.

Your work here literally powers modern life. You're not building apps that run on the network; you're building the AI that is the network's brain, managing global connectivity and data flow in real-time. This places you at a unique intersection of cutting-edge telecommunications and machine learning, a niche with immense growth potential as the world becomes increasingly dependent on seamless, intelligent connectivity.

Texas Instruments

Texas Instruments offers a uniquely hardware-centric path in the AI landscape. The focus here isn't on training massive models in the cloud but on the intricate art of shrinking and optimizing them to run efficiently on TI's low-power semiconductor chips. This is the world of embedded AI, where intelligence lives and makes decisions directly on the device itself.

Engineers work at the intersection of software and silicon, developing AI for signal processing, computer vision in industrial automation, and algorithms for automotive radar systems. The tech stack reflects this reality, requiring deep knowledge of C/C++, Python, MATLAB, and frameworks like PyTorch tailored for severe resource constraints. You'll collaborate directly with hardware designers, understanding the physics of the chip executing your code. This specialized expertise commands competitive salaries, with Systems/ML Engineers earning $120k to $165k and senior principal engineers reaching $220k.

The interview process is famously rigorous, designed to test this unique blend of skills. As highlighted in resources like a TI selection process guide, it evaluates deep knowledge of computer architecture, signal processing (like Fourier transforms), and the practical challenges of deploying models "on-silicon." Candidates report on Glassdoor that the interviews are highly technical and detailed.

You are fundamentally redefining where AI lives. Instead of sending sensor data to the cloud for processing, you're enabling it to be analyzed instantly on a motor, a camera, or a car's radar module. This role is for the engineer fascinated by the marriage of algorithm and hardware, who wants to understand not just the math, but the physical platform that brings it to life.

Intuit

Intuit's Plano office is a key hub for its mission to democratize financial management through AI. The unique challenge here isn't just building powerful models, but creating explainable AI that users can trust with critical decisions about their taxes, accounting, and cash flow. A black-box algorithm suggesting a tax deduction isn't enough; the system must articulate its reasoning in human-understandable terms.

Projects focus on automating and clarifying complex tasks. Teams develop conversational AI assistants for TurboTax, NLP models for transaction categorization in QuickBooks, and time-series forecasting for small business finances. The stack leverages Python, Java, AWS, and modern GenAI frameworks. This push for transparency makes Intuit a pioneer in ML interpretability, a frontier that's becoming increasingly crucial as noted in industry analyses of leading AI platforms.

For 2026, Machine Learning Engineers can expect salaries from $135k to $175k, with senior principal roles reaching $245k+. The interview process is distinctive, featuring a "Craft Demo" where candidates present a past project in depth. As detailed in resources like Prepfully's 2026 interview guide, this is paired with live system design sessions that test both high-level architecture and low-level implementation details.

You get to work on products with a direct, positive impact on financial well-being. The goal is to make sophisticated AI feel personal, accessible, and trustworthy - turning complex data into clear, actionable insights for millions of users navigating their financial lives.

Amazon

While its HQ2 anchors nearby Arlington, Amazon maintains a massive and growing AI presence across the DFW area, with numerous teams in Plano and Dallas. For an AI engineer, this means the scope is virtually unlimited, spanning from building the core AI/ML services on AWS to optimizing recommendation engines for billions of customers on Prime Video and Ads.

The work varies dramatically by team. You could be developing the next generation of Amazon SageMaker, creating computer vision for "Just Walk Out" technology, or crafting deep learning models for planetary-scale logistics optimization. The stack is deeply integrated with the native AWS ecosystem - tools like Sagemaker, Bedrock, and Lambda - with Python and Java as primary languages. This ecosystem is a major draw, as building these tools offers a meta-perspective on the entire industry.

Compensation is among the highest in the region. For 2026, an L5 (SDE II/MLE) can expect total compensation ranging from $180k to $240k, while L6 (Senior) roles reach $250k to $380k+, as tracked by compensation platforms. The interview process is legendary for its dual focus on rigorous system design/coding assessments and behavioral evaluations based on Amazon's Leadership Principles.

You are operating at a scale few companies can match, with the autonomy of the "two-pizza team" structure giving significant ownership over projects. Whether you're on an infrastructure team building platforms for the world's AI engineers or on a product team shaping the future of retail and media, your work will have immediate and substantial impact.

JPMorgan Chase & Co.

JPMorgan Chase's primary technology center in Plano serves as a command hub for AI that powers the global financial system. The firm treats artificial intelligence as a core strategic capability, with dedicated "AI Research" and "Applied AI" groups working across its investment bank, consumer bank, and asset management divisions to manage risk, discover insights, and serve clients.

The problems are as high-stakes as they come. Engineers build systems for algorithmic trading, develop RAG-based solutions to help investment bankers synthesize vast research libraries, and create AI agents for real-time fraud detection and credit risk management. The tech stack is enterprise-grade, utilizing Python, Java, Databricks, and specialized tools for GenAI and graph databases. The firm is actively hiring for critical roles, including Lead Security Engineer - Artificial Intelligence positions in Plano to secure these advanced systems.

The compensation reflects the premium placed on this domain expertise. For 2026, Associates earn $150k to $180k, while Vice Presidents and senior leads command $190k to $260k+, with data from platforms like Levels.fyi confirming these competitive ranges. The interview process typically involves resume-based technical calls, live coding assessments, and behavioral rounds focused on the STAR method to evaluate structured problem-solving.

This environment offers a unique playground defined by unparalleled data scale - petabytes of global financial transactions - where the cost of a model error is immense. You are working on defining the future of finance itself, whether through autonomous trading systems or personalized wealth management, all within the robust, innovative ecosystem of a global banking leader.

Capital One

Capital One's massive Plano campus operates what is widely considered one of the most sophisticated machine learning infrastructures in the financial sector. Unlike traditional banks that graft AI onto legacy systems, Capital One is engineered from the ground up to treat ML as a first-class citizen in its software delivery and decision-making processes, fostering what industry observers call a true "fail fast" tech culture within a highly regulated environment.

Engineers work on real-time fraud detection systems, credit risk modeling using advanced NLP for document analysis, and hyper-personalized financial product recommendations. The stack is built for performance and innovation, using Python, Spark, AWS, and proprietary MLOps platforms. Teams operate through a hybrid model, blending a centralized Center for Machine Learning (CML) with embedded groups within specific business lines, allowing for both research depth and rapid product integration.

Total compensation is highly competitive, reflecting this innovative stance. Machine Learning Engineers earn $144k to $196k, with Senior and Lead MLEs reaching $210k to $350k+ in total compensation, as detailed on salary aggregation sites like Levels.fyi.

The company is famous for its unique "Power Day" interview, which features a specialized ML case interview. As outlined in guides on the Capital One interview process, candidates are expected to design an end-to-end solution to a business problem, testing their ability to own a commercial outcome, not just tune a model. This approach seeks engineers who blend technical mastery with sharp business acumen.

Toyota Motor North America

Toyota Motor North America's headquarters and its data-driven subsidiary, Toyota Connected, represent the pinnacle of applied AI with a physical impact in Plano. The focus on "Mobility for All" leverages artificial intelligence to make transportation safer, more efficient, and deeply personalized, building the intelligent brain for next-generation vehicles.

This is where AI meets the road - literally. Engineers develop autonomous driving perception and planning systems, build predictive maintenance models by analyzing streams of vehicle sensor data, and create personalized in-car experiences. The tech stack is cutting-edge and production-tested, combining Python, PyTorch, TensorFlow, and cloud platforms like AWS (Sagemaker, Bedrock) with data tools like Snowflake. Salaries are strong for this specialized field, with Engineers earning $115k to $150k and Senior MLEs/Applied Scientists commanding $160k to $210k+.

The interview process is multi-round and structured, designed to assess both practical skill and theoretical knowledge. As reported on Glassdoor, it often involves a technical assessment, deep-dive project reviews, and theory discussions on topics like neural network optimization and system architecture. Further insights into the company's technical culture can be found on review pages for Toyota North America.

You are building AI that interacts with the physical world at a scale few can match, with your code directly impacting the safety and experience of millions of drivers. The problems are profoundly multidisciplinary, blending robotics, large-scale time-series analysis, and human-centered design. It's a chance to shape the future of transportation from a global corporate headquarters right here in Plano, backed by the manufacturing and engineering prowess of one of the world's largest automakers.

Finding Your Perfect Fit

A great menu presents enticing choices, but the perfect order is always personal. In Plano's thriving AI landscape, the "dishes" range from building the brain of a self-driving car to securing global financial markets. The real task isn't to pick the #1 ranked company, but to identify which unique mission, data challenges, and team culture align with your own professional appetite.

Use the details - the tech stacks, project types, and interview styles - as your tasting notes. Are you drawn to the tangible, physical-world impact at Toyota or PepsiCo, or the massive-scale digital systems at Capital One or Amazon? Does the variety of consulting at NTT DATA excite you more than the deep specialization in edge AI at Texas Instruments? Your career satisfaction will hinge on this fit more than any ranking.

Remember, your decision extends beyond the job description. Building your life in the DFW metro area, with no state income tax and a lower cost of living than coastal hubs, is a significant long-term advantage. You're positioning yourself within a dense and growing network, as Plano and its neighbors continue to be a top destination for AI companies and talent.

As the market evolves, so do the opportunities. Industry analysts note that compensation is increasingly influenced by AI-driven forecasting tools, making it crucial to understand your value. Let this list be your starting menu. Dig deeper, connect with engineers in your target roles, and find the position where your work will not only be cutting-edge but deeply meaningful to you. Your perfect fit is waiting to be ordered.

Frequently Asked Questions