Applied Machine Learning Engineer, Platform Architecture

Socket.dev

Cupertino (CA)

On-site

USD 180,000 - 240,000

Full time

4 days ago
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Job summary

Socket.dev seeks an AI/ML Engineer to turn hardware data into architectural insight for next‑gen Apple‑like SoCs. You will study and improve performance and power across the full product lifecycle, partnering with silicon and OS teams to implement changes on real silicon and ship them.

Ideal candidates blend research and shipping product, with large‑scale data and ML experience. You will apply ML techniques to vast telemetry, work in Python and modern DL frameworks, and contribute to the

Qualifications

  • Bachelor or higher in CS/CE/EE or related field.
  • Experience deploying ML systems in production.
  • Experience applying ML to large real-world datasets.
  • Python programming and modern DL frameworks.

Responsibilities

  • Turn complex hardware data into architectural insight.
  • Study and improve performance and power behavior of modern SoCs across the full product lifecycle.
  • Work with silicon and OS teams to implement changes on real silicon and bring them to ship.
  • Combine ML research with hands-on engineering at the intersection of data, system architecture, and ML.

Skills

Applied ML
Production ML systems
Python
Deep learning
Data analysis
ML in hardware

Education

B.S. in Computer Science/Engineering
M.S./Ph.D. in CS/CE/EE

Tools

C/C++ modeling infrastructure

Job description

Join the SoC Architecture team building ML and generative AI systems that shape how future Apple silicon is architected and tuned. We're looking for an AI/ML Engineer who can turn complex hardware data into architectural insight. You will apply that expertise to studying and improving the performance and power behavior of modern System-on-Chip designs across the full product lifecycle: ML-driven research to identify what should change in hardware or software, hands‑on partnership with silicon and OS teams to implement and bring those changes up on real silicon, and seeing them through to ship. This role is ideal for a hands‑on ML engineer who is energized by both research and shipping product, and who thrives at the intersection of large‑scale data, system architecture, and ML.

Description

You will join a multidisciplinary team of ML, software, and architecture engineers building systems that drive architectural exploration and tuning for current and future Apple SoCs. The work targets the full performance‑power tradeoff space across fabric, memory subsystem, system caches, dynamic voltage and frequency state control, clock and power gating policies, sleep state controls, and bottleneck prevention.

Minimum Qualifications
  • B.S. in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
  • Applied ML industry experience deploying complex ML systems in production.
  • Experience applying modern ML techniques to large real‑world datasets.
  • Programming experience in Python and experience in modern deep learning frameworks.
Preferred Qualifications
  • Working knowledge of SoC compute, memory, and power‑management subsystems, how real workloads exercise them, and the C/C++ modeling infrastructure typical of SoC environments.
  • Depth in time‑series analysis, including feature engineering on streaming telemetry.
  • Experience applying ML beyond prediction, including driving decisions, optimizing policies, and efficiently searching large configuration spaces.
  • Track record of training large‑scale models across distributed clusters.
  • Experience building stateful, multi‑turn agentic frameworks and complex execution flows.
  • M.S. or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a related field and 10+ years of relevant experience.
  • Track record of moving quickly from hypothesis to result and iterating based on evidence.
  • Excellent communication and collaboration skills to work effectively across technical disciplines.
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