Cirrus Logic · 1 day ago
Embedded Machine Learning Engineer (AI/ML)
Austin, TX
Full-time
Onsite
Lead/Staff
8+ years expCirrus Logic is a leading supplier of low-power, high-precision mixed-signal processing solutions for mobile and consumer applications. In this role, you will be a hands-on technical leader shaping machine learning programs, driving the development of ML models and prototypes for Edge and mixed-signal systems.
Enterprise SoftwareReal TimeSoftwareSpeech Recognition
Responsibilities
Lead rapid prototyping of ML models for edge intelligence across Voice, Sense, and Control domains, tightly integrated with Cirrus Logic’s mixed-signal processing strengths
Build datasets, design model architectures, and optimize performance, efficiency, and interpretability. Explore advanced approaches in ML-augmented signal processing, anomaly detection, and adaptive control
Collaborate with silicon, firmware, and systems teams to co-design ML architectures that operate efficiently on constrained hardware and embedded systems, balancing algorithmic accuracy with compute and power budgets
Stay at the forefront of ML frameworks, foundation/SLM trends, and physical-world AI applications. Scout external IP, academic work, and startups to inform CVL’s ML strategy
Provide guidance and technical direction to away-team engineers and contributors across Cirrus Logic. Share best practices in ML model lifecycle, from experimentation to deployment
Work hand-in-hand with Innovation Managers, advisory teams, customers, and external partners to identify opportunities, define success criteria, and validate ML-enabled innovations in real-world scenarios
Help define benchmarks, evaluation metrics, and pass/fail criteria that ensure ML prototypes address significant industry problems with clear paths to monetization
Qualification
Required
Master's or Ph.D. in Computer Science, Electrical Engineering, or related field with a focus on ML/AI
8+ years of hands-on experience developing and deploying ML systems on the Edge and within embedded platforms, including ownership of datasets, model development, and deployment pipelines
Proven experience implementing ML inference on resource-constrained systems such as microcontrollers, embedded SoCs, or custom silicon
Demonstrated experience with CNNs, RNNs (LSTM/GRU), and Transformer-based models, including custom architecture design and optimization for production
Experience tailoring these architectures for low-latency and low-power embedded inference
Strong understanding of representation learning, attention mechanisms, sequence-to-sequence modeling, and generative architectures
Ability to translate these methods into efficient implementations suited for real-time sensor, audio, or control workloads
Experience with quantization, pruning, knowledge distillation, mixed-precision training, and compiler-level optimizations to deploy models on CPUs, DSPs, NPUs, or hybrid SoC architectures
Familiarity with memory hierarchy tradeoffs, compute-offload, and bandwidth constraints in embedded ML
Proficiency in embedded software and firmware development (C/C++/Python) with experience integrating ML inference engines into real-time embedded stacks, RTOS environments, or bare-metal systems
Understanding of firmware pipelines, peripheral I/O, and signal-path integration for ML-augmented mixed-signal systems
Ability to design labeling strategies, synthetic data generation, and augmentation pipelines to support robust model development
Understanding of data acquisition and preprocessing directly from embedded sensors
Proven track record of co-designing ML and firmware solutions alongside hardware teams, balancing algorithmic, architectural, and physical constraints
Familiarity with embedded ML frameworks and toolchains (e.g., TensorRT, ONNX Runtime, TVM, CoreML, TFLite, Glow, Edge Impulse)
Ability to translate complex ML concepts into actionable insights for cross-disciplinary teams of algorithm, firmware, and hardware engineers
Preferred
Background in early-stage, high-ambiguity environments; experience contributing to incubation of new products or platforms
Experience in one or more of: generative models for voice, time-series/sequence modeling, anomaly detection for sensors, reinforcement learning for control systems
Familiarity with MLOps frameworks, data labeling pipelines, and distributed training
Experience collaborating with startups, academic labs, or open-source communities
Ability to assess the business and monetization value of ML solutions in emerging markets
Company
Cirrus Logic
Cirrus Logic is an industry leader in low-power audio and high-performance mixed-signal processing technology that creates immersive user experiences for the world’s top mobile and consumer applications.
1001-5000 employees
H1B Sponsorship
Cirrus Logic has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (3)
2024 (7)
2023 (4)
2022 (9)
2021 (8)
2020 (3)
Funding
Current Stage
Late StageTotal Funding
$5.8M2017-04-01Acquired
2016-02-11Debt Financing· $0.23M
2015-03-24Series Unknown· $0.58M
Leadership Team
Melissa Miccichi PHR, SHRM-CP
Senior HR Business Partner
Recent News
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