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Full Time Edge Ai Machine Learning Jobs (NOW HIRING)

... Machine Learning Engineer. * Profound experience in optimizing ML models and systems for Edge ... The range of annual base salary for full-time employees for this position is below. Please note ...

The AI/Machine Learning Engineer II will be part of the R&D team at Masimo with focus on design and ... It is a cutting-edge research and development opportunity with the potential to improve people ...

The AI/Machine Learning Engineer II will be part of the R&D team at Masimo with focus on design and ... It is a cutting-edge research and development opportunity with the potential to improve people ...

As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and ...

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$110K - $152K/yr

Masimo Wearables is seeking a Senior Engineer, AI/Machine Learning to join their R&D team focused ... cutting edge of technology through the generation of patentable ideas • Work with cross ...

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Full Time Edge Ai Machine Learning information

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$25.5K

$42.6K

$88K

How much do full time edge ai machine learning jobs pay per year?

As of Jul 21, 2026, the average yearly pay for full time edge ai machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What are Full Time Edge AI Machine Learning jobs?

Full Time Edge AI Machine Learning jobs involve developing and deploying machine learning models that run directly on edge devices, such as smartphones, IoT devices, or embedded systems, rather than relying solely on cloud computing. Professionals in these roles work on optimizing algorithms for low-power, resource-constrained environments and enabling real-time AI processing at the device level. These jobs typically require expertise in AI, machine learning, embedded systems, and sometimes hardware integration, and are essential for applications like smart cameras, autonomous vehicles, and industrial automation.

What are the key skills and qualifications needed to thrive as a Full Time Edge AI Machine Learning Engineer, and why are they important?

To thrive as a Full Time Edge AI Machine Learning Engineer, you need a solid background in computer science, machine learning algorithms, and embedded systems, often supported by a relevant degree and experience in AI model deployment. Familiarity with frameworks like TensorFlow Lite, ONNX, and hardware platforms such as NVIDIA Jetson or ARM Cortex is typically required, along with knowledge of programming languages like Python and C++. Strong problem-solving, adaptability, and effective communication skills help you collaborate across multidisciplinary teams and address real-time deployment challenges. These combined skills ensure efficient, scalable, and robust AI solutions on resource-constrained edge devices, which is critical for success in this rapidly evolving field.

What is the difference between Full Time Edge Ai Machine Learning vs Data Scientist?

AspectFull Time Edge Ai Machine LearningData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with ML frameworksBachelor's or Master's in CS, Statistics, or related fields; strong programming skills
Work EnvironmentEdge devices, IoT environments, real-time data processingOffice or remote, data analysis, model development
Industry UsageAI hardware companies, IoT, autonomous systemsTech, finance, healthcare, research

Full Time Edge Ai Machine Learning specialists focus on deploying ML models on edge devices for real-time processing, often requiring knowledge of hardware and embedded systems. Data Scientists analyze data, develop models, and interpret results primarily in cloud or office settings. While both roles involve machine learning, Edge AI emphasizes deployment on hardware, whereas Data Scientists focus on data analysis and model development.

What are some common challenges faced when deploying AI models on edge devices in a full-time Edge AI Machine Learning role?

One of the main challenges in this role is optimizing machine learning models to run efficiently on resource-constrained edge devices, which often have limited processing power and memory compared to cloud environments. Ensuring low latency and real-time performance without sacrificing accuracy requires specialized techniques such as model quantization or pruning. Additionally, maintaining robust security and handling data privacy on distributed devices adds complexity. Collaboration with hardware engineers and software developers is frequently required to address these multidisciplinary challenges.
More about Full Time Edge Ai Machine Learning jobs
What cities are hiring for Full Time Edge Ai Machine Learning jobs? Cities with the most Full Time Edge Ai Machine Learning job openings:
What are the most commonly searched types of Edge Ai Machine Learning jobs? The most popular types of Edge Ai Machine Learning jobs are:
Infographic showing various Full Time Edge Ai Machine Learning job openings in the United States as of July 2026, with employment types broken down into 67% Full Time, 22% Part Time, and 11% Contract. Highlights an 59% Physical, 3% Hybrid, and 38% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Staff Machine Learning Engineer - Edge AI

Staff Machine Learning Engineer - Edge AI

Samsara

Remote

Full-time

Re-posted 25 days ago


Job description

Who we are
Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing - and we are excited to help digitally transform their operations at scale.
Working at Samsara means you'll help define the future of physical operations and be on a team that's shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you'll have the autonomy and support to make an impact as we build for the long term.
About the role:
The Samsara AI team builds end-to-end AI solutions for our customers as well as core ML infrastructure for Samsara. As a Staff Machine Learning Engineer, you will be working with petabyte-scale sensor, diagnostic, video, and text data to solve critical problems for Physical Operations customers, globally. You will work closely with ML Engineers and Scientists, as well as full-stack and firmware engineers to deliver core product features, services, and optimizations.
This is a remote position open to candidates residing in the United States. This position requires travel up to 5% of the time. Relocation assistance will not be provided for this role.
You should apply if:
  • You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact-helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely.
  • You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world's physical operations.
  • You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go.
  • You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes.
  • You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we're all racing toward our connected operations vision, and we intend to win-together.
In this role, you will:
  • Lead design and implementation of critical AI product initiatives on Edge devices.
  • Develop both tactical AI solutions as well as more strategic and longer term research.
  • Work with petabyte-scale data from customer operations including text, transactions, diagnostics, sensor, camera, and location data.
  • Partner across business units to explore and prototype new AI experiences and optimize the ML model performance on edge devices.
  • Stay connected to industry and academic research and adopt novel technology that suits Samsara's needs.
  • Champion, role model, and embed Samsara's cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices

Minimum requirements for the role:
  • 8+ years experience as a Machine Learning Engineer.
  • Profound experience in optimizing ML models and systems for Edge compute constraints.
  • Coding in python or similar.
  • Coding in C++ or Rust.
  • Strong functional knowledge of the iterative machine learning product development process.
  • Experienced in developing and shipping production code at large scale.
  • Ability to distill informal or ambiguous customer and business requirements into crisp problem definitions.
  • Proven ability to communicate verbally and in writing to technical peers and leadership teams with various levels of technical knowledge.
  • Experience coaching and mentoring ML Engineers.

An ideal candidate also has:
  • Proficiency in self-serving with data for experiments and model training at scale.
  • An established record of successful high impact deliveries in AI.
  • Deep knowledge in state of the art Computer Vision and multi-model models.

The range of annual base salary for full-time employees for this position is below. Please note that base pay offered may vary depending on factors including your city of residence, job-related knowledge, skills, and experience. This role is also eligible for an initial RSU grant with no vesting cliff, and ongoing refresh opportunities tied to performance, subject to plan terms and conditions. Learn more about our total rewards and benefits below.
Annual Base Salary
$178,640-$319,000 USD
Total Rewards
At Samsara, we build for the people who keep the global economy moving. We want owners, not passengers, which is why our rewards are designed to fuel high-impact builders. Our compensation program delivers above-market total compensation through a combination of base salary, performance-based bonus/variable pay, and equity (for eligible roles) in a high-growth public company. We meaningfully differentiate pay for our top performers, who have the opportunity to earn above-market compensation that can outpace the broader market over time.
Beyond compensation, we provide the foundations that enable long-term success: a flexible, employee-led remote model, a professional development stipend, comprehensive health and parental leave plans, and more. If you're ready to build for the long term and own the outcome, your journey starts here.
Flexible Working
At Samsara, we embrace a flexible working model that caters to the diverse needs of our teams. Our offices are open for those who prefer to work in-person and we also support remote work where it aligns with our operational requirements. For certain positions, being close to one of our offices or within a specific geographic area is important to facilitate collaboration, access to resources, or alignment with our service regions. In these cases, the job description will clearly indicate any working location requirements. Our goal is to ensure that all members of our team can contribute effectively, whether they are working on-site, in a hybrid model, or fully remotely. All offers of employment are contingent upon an individual's ability to secure and maintain the legal right to work at the company and in the specified work location, if applicable.
Belonging at Samsara
At Samsara, we welcome everyone regardless of their background. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, protected veteran status, disability, age, and other characteristics protected by law. We depend on the unique approaches of our team members to help us solve complex problems and want to ensure that Samsara is a place where people from all backgrounds can make an impact.
Accommodations
Samsara is an inclusive work environment, and we are committed to ensuring equal opportunity in employment for qualified persons with disabilities. Please email accessibleinterviewing@samsara.com or click here if you require any reasonable accommodations throughout the recruiting process.
Our Commitment to Authenticity
We use Tofu, a fraud detection tool, to validate the authenticity of applications and protect against identity fraud. This ensures we are connecting with real people and allows us to prioritize genuine candidates. Please see Samsara's Candidate Privacy Notice for more information.
Fraudulent Employment Offers
Samsara is aware of scams involving fake job interviews and offers. Please know we do not charge fees to applicants at any stage of the hiring process. Official communication about your application will only come from emails ending in @samsara.com, @us-greenhouse-mail.io or @mail3.guide.co. For more information regarding fraudulent employment offers, please visit our blog post here.