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Remote Embedded Ai Jobs (NOW HIRING)

Right Skale, Inc.

GCP AI Engineer

GCP AI Engineer - Full Time - Remote (Occasional Travel) We are seeking an experienced GCP AI/ML ... are embedded throughout the AI/ML lifecycle. • Provide technical leadership and thought ...

Majesco

Principal Architect

As leaders in intelligent SaaS solutions, we've embedded AI and Agentic AI throughout our robust ... Remote - United States Are you an experienced insurance technology architect who can turn complex ...

Life360

Principal Product Manager, Embedded Devices

Life360 is a Remote-First company, which means a remote work environment will be the primary ... AI tool usage during interviews varies by role. You may be asked to demonstrate proficiency with AI ...

HealthEquity

Director, AI Enablement

$144K - $191K/yr

Ensure AI capabilities are embedded into the CX operating model and AI solutions are explainable ... Wellness program incentives Onboarding & Travel This is a remote role, with an in-person onboarding ...

Order.co

Business Process Analyst (Contract)

$45 - $60/hr

Order.co leverages embedded AI agents and embedded financial products to reinvent the way ... Location: Remote/Hybrid (based on business needs) * Reports to: SVP Strategy and Business ...

OneDigital

AI Builder - Remote

$90K - $115K/yr

Partner with embedded Product Managers to interpret business needs, prototypes, and early-stage AI builds * Take Product Manager-created concepts or prototypes and evolve them into production-ready ...

Upland Software, Inc.

Senior Account Executive

Our operating model has always supported remote work-and as we keep growing and evolving our ... choices (embedded AI vs. BYO-AI) with technical and business leaders. * Operational rigor ...

Elite Technology

Senior Business Analyst

$140K - $160K/yr

With embedded AI, predictive analytics, and integrated payments, Elite's products enable firms to ... Remote This role requires the individual to be based in Flexible across U.S. time zones.

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How much do remote embedded ai jobs pay per year?

As of May 31, 2026, the average yearly pay for remote embedded ai in the United States is $153,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Embedded AI Engineer, and why are they important?

To thrive as a Remote Embedded AI Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++, Python, or TensorFlow Lite, often supported by a degree in computer engineering or related fields. Familiarity with real-time operating systems (RTOS), edge AI development platforms, and version control tools such as Git is typically required. Strong problem-solving skills, effective remote communication, and self-motivation help you excel in collaborative yet independent work environments. These competencies are crucial for building efficient, innovative AI solutions on hardware platforms while ensuring seamless teamwork across distributed teams.

What are some common challenges faced by Remote Embedded AI Engineers, and how can they be overcome?

Remote Embedded AI Engineers often encounter challenges such as limited access to hardware for testing, asynchronous communication with distributed teams, and integrating AI models within resource-constrained embedded systems. Overcoming these challenges involves utilizing remote debugging tools, setting up robust simulation environments, and maintaining clear, regular communication with team members. Collaboration platforms and thorough documentation help ensure smooth coordination, while staying updated on best practices in embedded AI can address technical limitations.

What is a Remote Embedded AI engineer?

A Remote Embedded AI engineer is a professional who develops and integrates artificial intelligence (AI) algorithms into embedded systems, such as IoT devices, sensors, or smart appliances, while working from a remote location. Their role involves optimizing AI models to run efficiently on hardware with limited resources, ensuring reliable performance and low power consumption. These engineers typically collaborate with cross-functional teams to deliver intelligent, connected products, leveraging skills in machine learning, software development, and embedded hardware. Working remotely allows them to contribute to global projects without being tied to a specific office location.

What is the difference between Remote Embedded Ai vs Remote Machine Learning Engineer?

AspectRemote Embedded AiRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in Computer Science, Electrical Engineering, or related fields; experience with embedded systemsBachelor's or higher in Computer Science, Data Science, or related fields; strong programming and statistical skills
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsCloud platforms, data centers, software development environments
Industry UsageConsumer electronics, automotive, industrial IoTTech companies, finance, healthcare, research
Common Search/ComparisonYesNo

Remote Embedded Ai professionals focus on developing AI algorithms for embedded hardware and real-time systems, often working with IoT devices and specialized hardware. In contrast, Remote Machine Learning Engineers primarily develop models in cloud environments for data analysis and prediction. While both roles require strong programming skills, Embedded Ai emphasizes hardware integration, whereas Machine Learning Engineers focus on scalable model deployment.

More about Remote Embedded Ai jobs
What cities are hiring for Remote Embedded Ai jobs? Cities with the most Remote Embedded Ai job openings:
What are the most commonly searched types of Embedded Ai jobs? The most popular types of Embedded Ai jobs are:
What states have the most Remote Embedded Ai jobs? States with the most job openings for Remote Embedded Ai jobs include:
What job categories do people searching Remote Embedded Ai jobs look for? The top searched job categories for Remote Embedded Ai jobs are:
Remote Embedded Ai jobs near you
Infographic showing various Remote Embedded Ai job openings in the United States as of May 2026, with employment types broken down into 77% Full Time, 20% Part Time, and 3% Contract. Highlights an 9% Physical, 3% Hybrid, and 88% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.
GCP AI Engineer

GCP AI Engineer

Right Skale, Inc.

Remote

Full-time

Posted 3 days ago

Job description

GCP AI Engineer - Full Time - Remote (Occasional Travel)
We are seeking an experienced GCP AI/ML & Integration Engineer to design, build, and optimize enterprise-scale AI/ML solutions. The ideal candidate will have expertise in AI/ML architecture, integration services, model lifecycle management, and cloud-native deployments with a focus on Google Cloud Platform (GCP) technologies. This role requires both technical leadership and the ability to collaborate with cross-functional teams to deliver secure, scalable, and high-performing AI solutions.
Key Responsibilities
• Architect and implement end-to-end conversational AI and generative AI solutions leveraging Dialogflow CX, Vertex AI, and Vertex AI Agent Builder.
• Integrate AI services with Firebase, Firestore, Pub/Sub, Dataflow, and Cloud Run for real-time, data-driven applications.
• Establish MLOps best practices including CI/CD, model versioning, observability, governance, and security.
• Ensure compliance and responsible AI principles are embedded throughout the AI/ML lifecycle.
• Provide technical leadership and thought leadership on GCP AI/ML architecture and integration.
Key Skills
• 8+ years in enterprise architecture, with 2-3 years in GCP AI/ML and integration.
• Proficiency in Python (JavaScript a plus) for development and API integration.
• Hands-on expertise with Vertex AI, Dialogflow CX, Vertex AI Search and Conversation, RAG, Vector databases, and Vertex AI Model Garden.
• Strong knowledge of model development, tuning, deployment, evaluation, and governance frameworks on GCP.
• Experience and programming skills with data platforms and distributed data processing tools.
• Strong understanding of security, compliance, and responsible AI principles in Google Cloud.
• Familiarity with Kubernetes/GKE, CI/CD for AI/ML, and MLOps best practices using Vertex AI Pipelines, Cloud Build, and Artifact Registry, Cloud Logging, Cloud Monitoring, and Vertex AI Model Monitoring for observability and drift detection.
• Excellent communication and customer interfacing skills.
• GCP Professional Machine Learning Engineer certification preferred (will also consider Professional Cloud Architect willing to go for ML Engineer certification)
Job Type: Full Time
Work Type: US-based Remote with Occasional Travel
Time Zone: EST
Client Location: Concord, NH

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