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Edge Ml Jobs (NOW HIRING)

Edge AI ML Engineer

Framingham, MA ยท On-site

$150 - $200/hr

About the Role As an Edge AI ML Engineer, you will develop, optimize, and deploy machine learning models for audio and multimodal intelligence on real devices. You will work at the boundary of ML ...

Edge AI ML Engineer

Framingham, MA ยท On-site

$84K - $113K/yr

About the Role As an Edge AI ML Engineer, you will develop, optimize, and deploy machine learning models for audio and multimodal intelligence on real devices. You will work at the boundary of ML ...

AI Architect - Media

Atlanta, GA ยท On-site

$150 - $200/hr

Stay current with developments in AI/ML, including emerging architectures and edge inference techniques, and translate industry trends into practical, production oriented recommendations for ...

From Computer Vision to Generative AI and classic software engineering, maps data leverages cutting-edge ML techniques to process, interpret, and contextualize information from unstructured data ...

Work on cutting-edge ML inference framework project and optimize code for efficient and scalable ML inference using distributed compute strategies such as data, tensor, pipeline and expert ...

Stay current with developments in AI/ML, including emerging architectures and edge inference techniques, and translate industry trends into practical, production oriented recommendations for ...

You will play a critical role in defining technical strategy for developing, training, and deploying AI/ML models-particularly in edge ML and NPU enabled platforms-while collaborating closely with ...

Showing results 41-60

Edge Ml information

See salary details

$43.5K

$98.3K

$235K

How much do edge ml jobs pay per year?

As of Sep 9, 2026, the average yearly pay for edge ml in the United States is $98,344.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $107,000.00 per year, depending on experience, location, and employer.

What is the difference between Edge ML vs Data Scientist?

AspectEdge MLData Scientist
Required CredentialsKnowledge of machine learning, programming, and hardware integrationStatistics, programming, data analysis, often a degree in data science or related fields
Work EnvironmentEmbedded systems, IoT devices, real-time processing at the network edgeData analysis labs, corporate offices, cloud platforms
Industry UsageIoT, autonomous vehicles, smart devicesBusiness analytics, research, data-driven decision making

Edge ML specialists focus on deploying machine learning models directly on edge devices for real-time processing, often requiring hardware and software integration skills. Data scientists analyze data to extract insights, typically working in cloud or office environments. While both roles involve machine learning, Edge ML emphasizes deployment on hardware, whereas data scientists focus on data analysis and model development.

What other helpful pages are available for Edge Ml?

Other pages related to Edge Ml:

Infographic showing various Edge Ml job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $98,344 per year, or $47.3 per hour.

Edge AI ML Engineer

Framingham, MA โ€ข On-site

$150 - $200/hr

Other

Medical, Retirement

Posted 14 days ago


Job description

Job Description

At Bose Corporation, we believe sound is the most powerful force on earth - and for over 60 years, we have been a company built on innovation, excellence, and independence. Privately owned, fiercely customer-focused, and driven by our values, we continue to lead industries and transform lives through sound. Today, Bose Corporation is entering an exciting new era. Across multiple global Business Units and Global Functions, we are shaping the future of audio technology, automotive, luxury, and premium experiences. We invite you to join us in this transformation.

About the Team โ€“ Reference Software & ML Algorithms Group, System Engineering, Architecture & Platforms

We are building the algorithms, systems, and platforms that power the next generation of audio and multimodal experiencesโ€”from embedded devices to cloudโ€‘connected products. Our ambition is bold: to become the worldโ€™s Audio Lab - inventing, optimizing, and delivering meaningful and magical experiences anywhere sound matters. We sit at the intersection of digital signal processing (DSP), deep learning, embedded systems, and software infrastructure, turning new ideas into realโ€‘world capabilities across a wide range of hardware and product surfaces.

  • Invents and develops audio and multimodal ML algorithms for real-world product experiences.
  • Designs efficient neural networks and signal processing pipelines for embedded and onโ€‘device deployment.
  • Optimizes models for resourceโ€‘constrained hardware, including MCUs, DSPs, NPUs, and custom accelerators.
  • Build tools, infrastructure, and reference implementations that accelerate the journey from invention -> prototype -> product.
  • Learns from realโ€‘world deployment constraints to inform the next generation of algorithms, models, and platforms.
About the Role

As an Edge AI ML Engineer, you will develop, optimize, and deploy machine learning models for audio and multimodal intelligence on real devices. You will work at the boundary of ML modeling, DSP, and embedded systems, turning research concepts into efficient, robust, productionโ€‘ready algorithms. You will collaborate closely with ML researchers, DSP experts, firmware engineers, and hardware teams to design algorithms that perform well not only in the lab, but also under realโ€‘world constraints such as latency, memory and power. This role is ideal for an ML engineer who enjoys model development, experimentation, and algorithm design, while also caring deeply about whether those models can run efficiently on edge hardware.

In This Role, You WillML Modeling & Algorithm Development
  • Identify opportunities for new DSP/ML algorithms by deeply understanding device constraints, sensor characteristics, and hardware capabilities (MCU, DSP, NPU).
  • Develop audio and multimodal ML models for embedded and edge AI applications.
  • Design, train, evaluate, and iterate on models for realโ€‘world sensing and interaction use cases.
  • Prototype novel approaches that push whatโ€™s possible in lowโ€‘latency, onโ€‘device audio and multimodal processing.
Embedded / Onโ€‘Device Engineering
  • Develop software for RTOS environments (e.g., FreeRTOS) and deploy models to device runtimes and hardware accelerators (DSP, NPU, MCU).
  • Convert trained ML models into efficient embedded implementations (C/C++, quantization, fixedโ€‘point inference).
  • Optimize runtime performance: memory footprint, SRAM usage, latency, and power consumption.
  • Integrate ML inference into realโ€‘time firmware pipelines.
  • Design endโ€‘toโ€‘end embedded AI systems (sensor -> preprocessing -> model -> postโ€‘processing).
Platform & Performance Engineering
  • Architect reusable embedded ML platform components usable across multiple hardware targets.
  • Profile and optimize performance on MCUs, DSP cores, NPUs, and custom accelerators.
  • Work with crossโ€‘compilation toolchains, CMakeโ€‘based builds, and modular codebases.
  • Integrate with onโ€‘device ML runtimes (e.g., TFLite Micro, ExecuTorch, custom interpreters).
  • Provide actionable feedback on model architecture for deployment efficiency and realโ€‘time behavior.
Required Qualifications
  • Strong proficiency in C/C++ for embedded systems.
  • Strong experience developing and evaluating machine learning models, preferably for audio, speech, or other timeโ€‘series sensor data.
  • Experience optimizing ML models for edge, embedded, or resourceโ€‘constrained environments.
  • Proficiency in Python for model development, experimentation, evaluation, and tooling.
Preferred Qualifications
  • Masterโ€™s or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, or related field.
  • Experience with ML compilers/frameworks such as MLIR, Glow, ExecuTorch.
  • Experience with realโ€‘time streaming inference pipelines.
  • Knowledge of acoustics and classical audio DSP.
  • Experience with onโ€‘device ML (TinyML, quantization, pruning).
  • Publication track record in ML, DSP, systems, or embedded AI.
You Might Thrive Here If Youโ€ฆ
  • Love building systems where algorithms meet real hardware.
  • Enjoy profiling and optimizing code under tight compute and memory constraints.
  • Take ownership endโ€‘toโ€‘end - from prototype to hardware bringโ€‘up to production.
  • Thrive in fastโ€‘moving, ambiguous, zeroโ€‘toโ€‘one environments.
  • Want your work to directly shape the next generation of audioโ€‘driven experiences.

At Bose, you're inspired to be and do your best and are rewarded for your unique talents! Our compensation is thoughtfully tailored to your skills, experience, education, and location, and goes beyond base salary. The hiring range for this position in the primary work location of Framingham, Massachusetts is: $141,000-$193,950.The hiring range for other Bose work locations may vary. In addition to competitive base pay we offer rewards including bonus programs, comprehensive health and welfare benefits, a 401(k) plan, plus exclusive perks designed to support your wellbeing, and a generous employee discount where you can immerse yourself in our products and experiences. We are a proudly independent company - driven by purpose, guided by our values, and united by a belief in the power of sound. As the world leader in audio experiences, weโ€™re creating whatโ€™s next - pushing boundaries and delivering transformative sound experiences for people everywhere. Join us and make your next career move a mic-drop. Letโ€™s Make Waves.

Candidate Privacy Notice Candidate Terms & Conditions Cookie Notice Weโ€™re a company built on disruptive innovation - having the courage to challenge the status quo, an unwavering commitment to our customers, and the fundamental belief that anything is possible. We never settle; we have a passion for discovering better ways to help people enjoy the things they love. We need people like you, people with better solutions. If you join us, youโ€™ll find the opportunity to do your best work and the freedom to enjoy it. Here, every employee has the opportunity to build their own success and contribute to ours. Itโ€™s an atmosphere of trust, collaboration, high expectations, and great reward.

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