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Machine Learning Acceleration information

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How much do machine learning acceleration jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for machine learning acceleration in the United States is $21.33, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $22.84 per hour, depending on experience, location, and employer.

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

AspectMachine Learning AccelerationData Scientist
Required CredentialsKnowledge of hardware, programming, and ML frameworksDegree in CS, statistics, or related field; data analysis skills
Work EnvironmentTech companies, research labs, hardware firmsBusiness, tech, finance, healthcare sectors
Industry UsageOptimizing ML model training and inferenceAnalyzing data, building models, deriving insights

Machine Learning Acceleration focuses on enhancing the speed and efficiency of ML model training and deployment through hardware and software optimization. Data Scientists analyze data, develop models, and interpret results. While both roles involve machine learning, acceleration specialists optimize performance, whereas Data Scientists focus on data analysis and model development.

What other helpful pages are available for Machine Learning Acceleration?

Other pages related to Machine Learning Acceleration:

Infographic showing various Machine Learning Acceleration job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $44,363 per year, or $21.3 per hour.

Machine Learning System Hardware Architect

Sunnyvale, CA

Baidu USA
See more jobs at Baidu USAexternal

$285K/yr

Full-time

Re-posted yesterday

Job description

Do you want to be part of the AI revolution? Do you want to think out of the box, thriving on challenges in the AI industry and the desire to solve them? Do you want to work with a world-class team to explore the fast-growing AI hardware opportunities and impact on the AI industry?

We're looking forward to you joining us to collaborate, contribute, and revolutionize AI silicon and system.

Description

We are looking for a world-class Machine Learning System Architect (HW) to join our SoC team at Baidu's Sunnyvale office. The successful candidate will be a motivated self-starter who will thrive in this highly technical environment. Your job responsibilities as a Machine Learning System Architect will help the team to architect and create high-performance machine learning silicon and connect thousands of Kunlun Accelerators together for distributed AI training tasks.

Create differentiated architectural innovations for Baidu's Kunlun AI SoC roadmap. Architect, simulate, and design amazing machine learning solutions for our AI machine learning products.

Develop system-level ML architectures that push the boundaries of performance, power, and latency; collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance.

Monitor industrial and academic trends in artificial intelligence and determine where they should intersect our roadmaps. Drive partnerships for access to the most advanced AI technologies

Evaluate the power, performance, and cost of prospective architecture and subsystems. Build scalable tools for modeling and performance evaluation.

Engage with system and application software engineers to ensure optimization of the entire hardware/software stack.

Engage with SoC design, verification, and validation engineers to realize the architecture.

Qualifications

  • Knowledge of Machine Learning market, technological and business trends, software ecosystem, and emerging applications.
  • Proven track record 5+ years architecting hardware solutions for Machine Learning, acceleration and optimization.
  • Experience with deep learning frameworks including TensorFlow, PyTorch, PaddlePaddle, etc.
  • Strong track record of outreach to ML researchers and application developers.
  • Experience with CPUs, GPUs, memory systems, and accelerators.
  • Experience with performance simulation and modeling in C++
  • Experience with SoC interconnects and NoCs
  • Experience with area, frequency, and power optimizations
  • Familiarity with video, DSP, Ethernet, and PCIe
  • MS or PhD in Electrical or Computer Engineering.
  • Excellent communication skills in both English and Chinese.

Culture Fit:

  • Mission alignment: If you want to be part of a team to accomplish this great mission, we will provide you the best possible platform to do that.
  • Self-directed: We work best with people that are driven, motivated, and aspire to greatness.
  • Hungry to learn: We are eager to see you learn new skills and grow.
  • Team orientation: We work in small, fast-moving teams. We watch out for each other and go after big goals together as a team.

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