Ambiq · 6 hours ago
Sr. Staff Edge AI Applied Machine Learning Engineer
Austin, Texas, United States
Full-time
Onsite
Senior Level, Lead/Staff
5+ years expAmbiqmicroinc is a pioneer in ultra-low-power semiconductor solutions, aiming to enable intelligence everywhere. They are seeking an experienced Edge AI Applied ML Engineer to design, optimize, and deploy efficient on-device AI models for resource-constrained devices, helping accelerate the shift to on-device intelligence across various applications.
Consumer ElectronicsInternet of ThingsManufacturingSemiconductor
No H1B
U.S. Citizen Only
Responsibilities
Develop and optimize on-device ML models for constrained, real-time, battery-powered products, balancing accuracy with latency, memory, and energy
Build and maintain Ambiq’s open-source ADKs for modular datasets, models, tasks, and training recipes
Translate cutting-edge research into production-grade demos and reference implementations
Apply model efficiency techniques: quantization, compression, pruning, and structured sparsification
Serve as a domain expert in audio and vision (data strategy, evaluation, and failure analysis)
Port and optimize customer models to Ambiq edge runtimes, ensuring correctness, performance, and usability
Deliver and promote customer-ready assets: docs, tutorials, examples, benchmarks, plus white papers and conference representation
Qualification
Required
BS in Computer Science or related field + 5+ years of relevant experience (or equivalent practical experience)
Strong proficiency in Python; working proficiency in C/C++ and/or Rust for performance and runtime integration
Domain expertise in audio (KWS, speech enhancement, SLM, TTS) and/or vision (classify/detect/segment/pose/OBB/track), with DSP fundamentals (e.g., FFT)
Comfortable in Linux development with Docker/dev containers (able to work across Mac/Windows as needed)
Experience with one or more training frameworks: PyTorch, TensorFlow, JAX, Keras
Strong ML engineering fundamentals: data pipelines, augmentation, metrics, experiment reproducibility, and failure analysis
Familiarity with edge deployment stacks such as ONNX, LiteRT, ExecuTorch
Hands-on with edge optimization: quantization (PTQ/QAT), compression, and (structured) sparsification, plus profiling for latency/memory/energy tradeoffs
Efficient use of AI-assisted development tools while maintaining rigor (testing, review, reproducibility)
Must be currently authorized to work in the United States for any employer. We do not sponsor or take over sponsorship of employment visas (now or in the future) for this role
Preferred
MS or PhD in related disciplines (ML, EE, signal processing, computer vision, robotics) is highly desirable
Company
Ambiq
Ambiq® was founded in 2010 on the simple yet powerful notion that extremely low-power semiconductors are the key to the future of electronics.
201-500 employees
Funding
Current Stage
Public CompanyTotal Funding
$470.19MKey Investors
Q Venture PartnersOUP (Osage University Partners)Kleiner Perkins
2026-01-21Post Ipo Equity· $83.07M
2025-07-30IPO
2023-09-12Series Unknown· $83.22M
Leadership Team
Fumihide Esaka
Chief Executive Officer
Scott Hanson
Founder and CTO
Recent News
Business Wire
2026-01-23
2026-01-23
legacy.thefly.com
2026-01-22
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