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Amd Machine Learning Jobs in Texas (NOW HIRING)

Eaton

Field Application Engineer, Electronics

Austin, TX · On-site

$123K - $181K/yr

... AMD, AWS(machine learning), HPE, HPI, Meta, IFX and TI. The job requires frequent travel to various locations, collaborate with customers for product/project designing and developing. Visiting ...

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$12

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$28

How much do amd machine learning jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for amd machine learning in Texas is $21.26, according to ZipRecruiter salary data. Most workers in this role earn between $18.37 and $23.75 per hour, depending on experience, location, and employer.

What are some common challenges faced by machine learning engineers at AMD, and how can applicants prepare to address them?

Machine learning engineers at AMD often work on optimizing algorithms for high-performance hardware, which requires balancing model accuracy with computational efficiency. A common challenge is adapting complex models to run efficiently on specialized AMD hardware such as GPUs and accelerators. Applicants can prepare by gaining hands-on experience with parallel computing, understanding low-level hardware optimization, and becoming familiar with AMD’s development tools and frameworks. Collaboration with hardware engineers and software teams is also frequent, so strong communication and teamwork skills are essential.

What are AMD machine learning engineers?

AMD machine learning engineers are professionals who develop, optimize, and deploy machine learning models using AMD hardware and software platforms. They work on designing algorithms and frameworks that leverage AMD GPUs and accelerators for tasks such as data analysis, computer vision, and artificial intelligence. Their responsibilities often include collaborating with software developers, data scientists, and hardware engineers to ensure machine learning solutions run efficiently on AMD architecture.

What is the difference between Amd Machine Learning vs Data Scientist?

AspectAmd Machine LearningData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related fields; certifications like AWS, AzureBachelor's or higher in CS, Statistics, or related fields; certifications like SAS, Python
Work EnvironmentTech companies, R&D labs, AI startupsBusiness analytics, finance, healthcare, tech firms
Industry UsageDeveloping ML models, algorithms, AI solutionsData analysis, insights, predictive modeling
Common Search/ComparisonYesYes

While both roles involve working with data and algorithms, Amd Machine Learning focuses on developing machine learning models and AI solutions, often requiring specialized technical skills. Data Scientists analyze data to generate insights and support decision-making, with a broader scope that includes statistical analysis. Both roles are vital in tech-driven industries but differ in their primary focus and skill sets.

What are the key skills and qualifications needed to thrive as an AMD Machine Learning Engineer, and why are they important?

To thrive as an AMD Machine Learning Engineer, you need strong programming skills in Python or C++, a deep understanding of machine learning algorithms, and typically a degree in computer science or a related field. Familiarity with AMD hardware, GPU acceleration libraries like ROCm, and frameworks such as TensorFlow or PyTorch is essential. Analytical thinking, problem-solving, and effective collaboration are vital soft skills for excelling in this multidisciplinary environment. These skills ensure robust ML model development and optimization that leverage AMD hardware capabilities for high-performance computing applications.
What are popular job titles related to Amd Machine Learning jobs in Texas? For Amd Machine Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Amd Machine Learning jobs in Texas look for? The top searched job categories for Amd Machine Learning jobs in Texas are:
Amd Machine Learning jobs near you
Infographic showing various Amd Machine Learning job openings in Texas as of July 2026, with employment types broken down into 2% Locum Tenens, 34% Internship, 47% Full Time, 4% Part Time, 8% Contract, and 5% Summer. Highlights an 69% Physical, 5% Hybrid, and 26% Remote job distribution, with an average salary of $44,224 per year, or $21.3 per hour.
Technical Product Manager, AI Cloud Networking

Technical Product Manager, AI Cloud Networking

Mirantis

Austin, TX • On-site, Remote

$165K - $191K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Company Description
About Mirantis
Mirantis is the Kubernetes-native AI infrastructure company, enabling organizations to build and operate scalable, secure, and sovereign infrastructure for modern AI, machine learning, and data-intensive applications. By combining open source innovation with deep expertise in Kubernetes orchestration, Mirantis empowers platform engineering teams to deliver composable, production-ready developer platforms across any environment-on-premises, in the cloud, at the edge, or in sovereign data centers. As enterprises navigate the growing complexity of AI-driven workloads, Mirantis delivers the automation, GPU orchestration, and policy-driven control needed to manage infrastructure with confidence and agility. Committed to open standards and freedom from lock-in, Mirantis ensures that customers retain full control of their infrastructure strategy.
Job Description
Mirantis is looking for a Technical Product Manager to own networking for k0rdent AI, our control plane for GPU infrastructure and distributed AI workloads. In this role, you will define the networking strategy, roadmap, and feature priorities that determine how operators deploy, segment, and scale tenant networks across GPU clusters running large-scale training and inference.
GPU cloud networking sits at the intersection of high-performance computing and multi-tenant cloud, and the product must hold both worlds together. You will shape how k0rdent AI reasons about collective communication libraries (NCCL, RCCL, NVSHMEM), lossless east-west fabrics over InfiniBand and RoCEv2, and the north-south path through BGP-driven underlays, multi-tenant overlays, and programmable dataplanes accelerated by DPUs and SmartNICs from NVIDIA, AMD Pensando, and the broader ecosystem. These layers are typically operated as disconnected silos. Your job is to make them a coherent, declarative product.
The ideal candidate brings strong technical fluency in classical networking and the AI stack. You will work directly with engineering to shape requirements, with marketing to sharpen positioning, and with field teams to convert technical depth into wins in competitive GPU cloud and NeoCloud deals.
Responsibilities:
  • Own the vision, roadmap, and priorities for k0rdent AI networking, defining how customers design, automate, and operate every aspect of their network, including underlay fabric management, tenant connectivity, RDMA, DNS/IPAM, and more
  • Translate requirements from NeoClouds, GPU clouds, telcos, sovereign clouds, and enterprise platform teams into clear product direction
  • Partner with engineering and architecture to define requirements, evaluate trade-offs, and ship secure, scalable, reliable networking capabilities
  • Manage the networking backlog, using feedback from production deployments and design partners to refine roadmap priorities and positioning
  • Define positioning, packaging, and competitive differentiation for k0rdent AI networking
  • Create field-facing assets, including technical briefs, battlecards, and reference architectures; support strategic accounts as the networking product lead
  • Represent Mirantis at events, analyst briefings, and customer advisory boards; engage silicon, fabric, and ecosystem partners on reference architecture alignment

Qualifications
Qualifications:
  • 5+ years in product management, technical product management, or a senior technical role owning a networking product, platform, or large-scale automated network
  • Hands-on familiarity with BGP, VXLAN/EVPN, VRFs, OVS/OVN, SR-IOV, RDMA/RoCEv2 or InfiniBand, and DNS/IPAM at scale
  • Fluency in Linux networking, Kubernetes networking, SDN/overlay networking, hyperscale or service provider networking, or network automation
  • Hands-on experience with modern GPU cluster networking, including rail-optimized fabric design, GPUDirect RDMA and collective communication tuning (NCCL, RCCL, NVSHMEM), and DPU/SmartNIC offload

Why you'll love Mirantis:
  • Build the networking foundation for the AI cloud era, working directly with leading GPU cloud operators, NeoClouds, sovereign clouds, and AI-first enterprises
  • Collaborate with a world-class, distributed team committed to openness and technical excellence
  • Shape the product narrative and influence go-to-market success

Additional Information
What does Mirantis offer you?
  • Work with an established Silicon Valley leader in the cloud infrastructure industry.
  • Work with exceptionally passionate, talented and engaging colleagues, helping Fortune 500 and Global 2000 customers implement next-generation cloud technologies.
  • Be a part of cutting-edge, open-source innovation.
  • Thrive in the high-energy environment of a young company where openness, collaboration, risk-taking, and continuous growth are valued.
  • Professional development and training.
  • Attend conferences and working groups.
  • Customized workstation (macOS, Windows).
  • A competitive compensation package with strong benefits plan and stock options.

It is understood that Mirantis, Inc. may use automated decision-making technology (ADMT) for specific employment-related decisions. Opting out of ADMT use is requested for decisions about evaluation and review connected with the specific employment decision for the position applied for. You also have the right to appeal any decisions made by ADMT by sending your request to isamoylova@mirantis.com
By submitting your resume, you consent to the processing and storage of your personal data in accordance with applicable data protection laws, for the purposes of considering your application for current and future job opportunities.
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