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Amd Machine Learning Jobs (NOW HIRING)

Voltai

Machine Learning Engineer

Palo Alto, CA · On-site

About the Team Backed by Silicon Valley's top investors, Stanford University, and CEOs/Presidents of Google, AMD, Broadcom, Marvell, etc. We are a team of previous Stanford professors, SAIL ...

Voltai, Inc

Machine Learning Engineer

Palo Alto, CA · On-site

About the Team Backed by Silicon Valley's top investors, Stanford University, and CEOs/Presidents of Google, AMD, Broadcom, Marvell, etc. We are a team of previous Stanford professors, SAIL ...

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How much do amd machine learning jobs pay per hour?

As of Aug 5, 2026, the average hourly pay for amd machine learning in the United States is $22.82, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $25.48 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 is an AMD machine learning engineer?

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?

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.
More about Amd Machine Learning jobs
What cities are hiring for Amd Machine Learning jobs? Cities with the most Amd Machine Learning job openings:
What states have the most Amd Machine Learning jobs? States with the most job openings for Amd Machine Learning jobs include:
What job categories do people searching Amd Machine Learning jobs look for? The top searched job categories for Amd Machine Learning jobs are:
Amd Machine Learning jobs near you
Infographic showing various Amd Machine Learning job openings in the United States as of July 2026, with employment types broken down into 3% Locum Tenens, 33% Internship, 43% Full Time, 2% Part Time, 15% Contract, and 4% Summer. Highlights an 62% Physical, 8% Hybrid, and 30% Remote job distribution, with an average salary of $47,468 per year, or $22.8 per hour.

Machine Learning Engineer

Voltai

Palo Alto, CA • On-site

Full-time

Re-posted 20 days ago

Job description

About Voltai
Voltai is developing world models, and agents to learn, evaluate, plan, experiment, and interact with the physical world. We are starting out with understanding and building hardware; electronics systems and semiconductors where AI can design and create beyond human cognitive limits.

About the Team

Backed by Silicon Valley’s top investors, Stanford University, and CEOs/Presidents of Google, AMD, Broadcom, Marvell, etc. We are a team of previous Stanford professors, SAIL researchers, Olympiad medalists (IPhO, IOI, etc.), CTOs of Synopsys & GlobalFoundries, Head of Sales & CRO of Cadence, former US Secretary of Defense, National Security Advisor, and Senior Foreign-Policy Advisor to four US presidents.

What we're Looking For

  • Strong AI/ML engineering skills from top tier CS, EECS, Math and Physics programs.

  • Proven track record of delivering AI/ML projects from concept to production.

  • Hands-on experience fine-tuning and deploying large language models (LLMs) in production environments.

  • Prior experience working with multi-modal models (e.g., combining text, image, or audio inputs).

Bonus Points

  • Background in competitive programming.

  • Contributions to open-source initiatives.

  • Notable awards or publications in leading journals/conferences.

  • Experience thriving in a fast-paced, hyper-growth startup environment.