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Amd Machine Learning Jobs in California (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 ...

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 ...

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How much do amd machine learning jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for amd machine learning in California is $22.52, according to ZipRecruiter salary data. Most workers in this role earn between $19.47 and $25.14 per hour, depending on experience, location, and employer.

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 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.

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 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 popular job titles related to Amd Machine Learning jobs in California?

For Amd Machine Learning jobs in California, the most frequently searched job titles are:

What job categories do people searching Amd Machine Learning jobs in California look for?

The top searched job categories for Amd Machine Learning jobs in California are:

What cities in California are hiring for Amd Machine Learning jobs?

Cities in California with the most Amd Machine Learning job openings:

Amd Machine Learning jobs near you
Infographic showing various Amd Machine Learning job openings in California as of August 2026, with employment types broken down into 94% Full Time, and 6% Temporary. Highlights an 90% In-person, 5% Hybrid, and 5% Remote job distribution, with an average salary of $46,846 per year, or $22.5 per hour.

AI Research Scientist, Reinforcement Learning (LLM) and Post-Training

AMD (Advanced Micro Devices)

Santa Clara, CA • On-site

Other

Posted 3 days ago

New

Advanced Micro Devices rating

8.6

Company rating: 8.6 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

27th of 157 rated electronics manufacturers

Job description

WHAT YOU DO AT AMD CHANGES EVERYTHING
At AMD, our mission is to build great products that accelerate next-generation computing experiences-from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you'll discover the real differentiator is our culture. We push the limits of innovation to solve the world's most important challenges-striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
THE ROLE:
We are hiring a AI Research Scientist, Reinforcement Learning (LLM) and Post-Training, specializing in reinforcement learning to advance post-training and interactive learning for large generative models applied to demanding engineering and hardware-adjacent tasks (code, optimization, tool use, and long-horizon decision making). You will invent and analyze RL algorithms-policy optimization, preference-based methods, exploration, credit assignment, and reward modeling-run rigorous empirical studies, and partner with infra and product teams to land methods that improve measurable task success without sacrificing stability or safety.
THE PERSON:
You publish and ship. You are fluent in both RL theory and the practical path from ablation to production-scale training. You care about reward misspecification, variance reduction, and evaluation that reflects real constraints-not only toy environments.
KEY RESPONSIBILITIES:
  • Research and develop RL methods for post-training LLMs and code models on structured engineering tasks with verifiable or preference-based feedback
  • Design reward models, curricula, and off-policy or on-policy training recipes suited to sparse, noisy, or expensive labels from experts and simulators
  • Characterize failure modes (reward hacking, degenerate policies, instability) and propose mitigations grounded in experiments
  • Collaborate with RL infra engineers to scale training; define interfaces for rollout generation, logging, and reproducibility
  • Publish at top venues (e.g. NeurIPS, ICML, ICLR) and contribute internal technical leadership on the RL roadmap

PREFERRED EXPERIENCE:
  • Strong publication record in reinforcement learning or closely related machine learning areas.
  • Hands-on experience training RL or preference-optimized models at non-trivial scale (GPUs, distributed jobs)
  • Experience with LLM post-training, RLHF/RLAIF, or policy optimization for language or code agents
  • Familiarity with compilers, kernels, EDA-style workflows, or large-scale codebases is a plus

ACADEMIC CREDENTIALS:
  • PhD in Computer Science, Machine Learning, or related field strongly preferred.

#LI-BM1
#LI-Hybrid
Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.
This posting is for an existing vacancy.

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