At a Glance
- Tasks: Lead the development of cutting-edge AI/ML systems for real-time applications.
- Company: Join Analog Devices, a global leader in semiconductor technology.
- Benefits: Enjoy competitive pay, great benefits, and a focus on work-life balance.
- Other info: Collaborative environment with opportunities for professional growth and innovation.
- Why this job: Shape the future of technology while working on impactful projects.
- Qualifications: Masters/PhD in Electrical Engineering with 6+ years in audio signal processing.
The predicted salary is between 63000 - 77000 £ per year.
About Analog Devices, Inc. (NASDAQ: ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world.
Join us at Analog Devices as a Staff AI/ML Embedded ML/DSP Systems Engineer and lead the development of cutting-edge AI/ML systems that power real-time applications across industries like industrial automation, data centers, communications, and hardware design. At Analog Devices, we’re committed to pushing the boundaries of innovation in Physical AI. Be at its forefront, working at the intersection of hardware and software to deliver scalable, production-grade solutions. This role offers the opportunity to drive technical strategy, mentor teams, and shape the future of AI/ML systems.
Key Responsibilities:
- Architect and optimize end-to-end deployment pipelines for compact audio AI models from trained model through quantization, profiling, and production deployment on DSP/NPU targets.
- Define and drive DSP/NPU partitioning strategies, balancing workload allocation, memory bandwidth, latency, and power across processing elements on the SoC.
- Own simulation-to-RTL validation flows: develop bit-exact reference models, collaborate with RTL teams on functional verification, and close gaps between algorithmic intent and hardware behavior.
- Perform low-level implementation and optimization of signal processing and neural network kernels for fixed-point DSP and NPU instruction sets, maximizing utilization of MAC arrays, SIMD paths, and on-chip memory hierarchies.
- Profile and optimize inference performance (cycles, memory footprint, power) under strict always-on and real-time constraints typical of hearable/wearable devices.
- Design and maintain model compression and quantization workflows (PTQ, QAT) with rigorous quality tracking against floating-point baselines.
- Develop signal processing algorithms for array processing, beamforming, and spatial filtering, with a clear path from MATLAB/Python prototypes to deployable fixed-point implementations.
- Contribute to audio ASIC system architecture definition — informing hardware spec decisions (precision, buffer sizes, DMA structures, NPU config) based on algorithmic and deployment requirements.
- Generate IP (patents) and represent the team's technical depth to OEM customers in automotive and hearable segments.
- Mentor engineers in deployment best practices, embedded optimization, and hardware-aware algorithm design.
Required Qualifications:
- Masters/PhD in Electrical Engineering, signal processing, or related field.
- 6+ years in audio/speech signal processing within a semiconductor environment, with significant hands-on deployment experience on DSP and/or NPU platforms.
- Demonstrated expertise in fixed-point algorithm implementation, model quantization (PTQ/QAT), and cycle-level optimization for resource-constrained processors.
- Strong working knowledge of simulation-to-RTL flows: bit-exact modeling, RTL co-simulation, and functional verification collaboration with design teams.
- Proficiency in C (embedded/firmware level), Python, MATLAB, and deep learning frameworks (TensorFlow/TFLite, PyTorch/ONNX).
- Experience with low-level profiling tools, instruction set architectures, and memory optimization for embedded AI inference.
Preferred Qualifications:
- Direct experience with NPU/accelerator architectures (dataflow engines, weight-stationary/output-stationary designs) and their programming models.
- Familiarity with ASIC development cycles — from algorithm freeze through tapeout and silicon validation.
- Background in always-on, sub-mW audio processing for hearable, TWS, or wearable products.
- Track record of patents in audio signal processing or embedded ML.
- Experience technically leading a small engineering team.
- Solid foundation in array signal processing, beamforming, and acoustic system design.
Why You’ll Love Working at ADI:
At Analog Devices, you'll be part of a collaborative and innovative team that's shaping the future of technology. We offer a supportive environment focused on professional growth, competitive compensation and benefits, work-life balance, and the opportunity to work on cutting-edge projects that make a real impact on the world. Your expertise will shape the future of technology, and you’ll be supported by a culture that values continuous advancement and professional growth.
Staff Embedded ML/DSP Systems Engineer (Audio Engineering) in Newbury employer: Analog Devices
Analog Devices is an exceptional employer that fosters a collaborative and innovative work culture, making it an ideal place for Senior Design Verification Engineers to thrive. With a strong emphasis on employee growth and development, the company offers numerous opportunities for professional advancement while working on cutting-edge mixed-signal products in the vibrant UK tech landscape. Employees benefit from a supportive environment that values communication and teamwork, ensuring a rewarding and meaningful career experience.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Embedded ML/DSP Systems Engineer (Audio Engineering) in Newbury
✨Join Local Tech Meetups
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We think you need these skills to ace Staff Embedded ML/DSP Systems Engineer (Audio Engineering) in Newbury
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Analog Devices.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Analog Devices and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Analog Devices
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Analog Devices uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.