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Artificial Intelligence Operator Jobs (NOW HIRING)

Ziply Fiber

Director, Artificial Intelligence (AI)

$165K - $200K/yr

Director, Artificial Intelligence (AI) Base Salary: $165,000 to $200,000 annually DOE Bonus: Target ... operating model that reduces fragmentation and accelerates enterprise-wide adoption. • Partner ...

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Artificial Intelligence Operator information

Which AI job is high paying?

High-paying AI jobs include roles such as AI Research Scientist, Machine Learning Engineer, and Data Scientist, often requiring advanced degrees and expertise in programming, statistics, and deep learning frameworks. These positions typically offer higher salaries due to their specialized skills and demand in industries like technology, finance, and healthcare.

What are some common challenges faced by Artificial Intelligence Operators when maintaining AI systems in a production environment?

Artificial Intelligence Operators often encounter challenges such as monitoring model performance, detecting data drift, and responding to unexpected system behaviors in real time. They must balance ensuring system uptime with the need to troubleshoot and optimize models as data and business needs evolve. Collaboration with data scientists, engineers, and IT staff is essential to quickly resolve incidents and implement updates or patches. Staying current with best practices in model deployment and ethical AI use also presents an ongoing learning curve.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior AI researcher, machine learning director, or executive role, with compensation including salary, bonuses, and stock options reaching that amount annually. These roles often require advanced skills in AI, deep learning, and data science, along with extensive experience and leadership responsibilities.

What is an AI operator's job?

An AI operator manages and monitors artificial intelligence systems, ensuring they function correctly and efficiently. They may troubleshoot issues, adjust parameters, and work with data and AI tools to optimize performance, often requiring knowledge of programming, machine learning, and system management.

What is the difference between Artificial Intelligence Operator vs Data Analyst?

AspectArtificial Intelligence OperatorData Analyst
Required CredentialsRelevant certifications in AI, machine learning, or data science; often a degree in computer science or related fieldDegree in statistics, mathematics, or related field; certifications in data analysis tools
Work EnvironmentTech companies, AI development labs, or data-driven organizations; working with AI models and algorithmsBusiness environments, research firms, or consulting; analyzing datasets and generating reports
Employer & Industry UsagePrimarily in AI and tech industries, focusing on AI system operation and maintenanceAcross various industries including finance, marketing, healthcare, focusing on data interpretation

While both roles involve working with data, Artificial Intelligence Operators focus on managing and maintaining AI systems, whereas Data Analysts interpret data to inform business decisions. The roles often overlap in skills but differ in their primary focus and tools used.

How much do AI operators make?

AI operators typically earn between $50,000 and $100,000 annually, depending on experience, location, and the complexity of tasks. Entry-level positions may start lower, while experienced operators working with advanced tools and machine learning models can earn higher salaries.

What is an Artificial Intelligence Operator?

An Artificial Intelligence Operator is a professional responsible for managing, monitoring, and maintaining AI systems and applications. They ensure that AI models perform as expected, troubleshoot issues, and optimize the deployment of AI solutions in various environments. Their role often involves working with data scientists, software engineers, and IT specialists to oversee the lifecycle of AI technologies, including updates, scaling, and compliance. Artificial Intelligence Operators play a crucial role in bridging the gap between AI development and practical, reliable operation in real-world settings.

What are the key skills and qualifications needed to thrive as an Artificial Intelligence Operator, and why are they important?

To thrive as an Artificial Intelligence Operator, you need a solid understanding of computer science fundamentals, data analysis, and AI concepts, typically supported by a relevant degree or technical training. Familiarity with AI platforms, machine learning frameworks (such as TensorFlow or PyTorch), and data management systems is essential, along with certifications in AI or cloud technologies being advantageous. Strong problem-solving abilities, attention to detail, and effective communication skills help operators adapt to rapidly changing technologies and collaborate with diverse teams. These skills ensure effective deployment, monitoring, and optimization of AI systems, enabling organizations to leverage AI solutions reliably and ethically.
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Artificial Intelligence Operator jobs near you
Artificial Intelligence Engineer

Artificial Intelligence Engineer

Harrison Clarke

Santa Rosa, CA • On-site

$250K - $400K/yr

Other

Medical, Dental, Vision, PTO

Posted 24 days ago

Job description

AI Engineer - Defense Robotics

Location: San Francisco (On-Site)

Compensation: $250,000 - $400,000 base + Equity


Most autonomy work never leaves the simulator. The model performs, the demo lands, and then it meets a real world environment and falls apart the first time the lighting is wrong or something moves that wasn't supposed to. This role is the opposite of that. The systems here run in the field, in real world environments, with people depending on the output.


An early-stage defense company is building the intelligence layer for fleets of robots: a foundation model that takes a natural-language command from a human operator and turns it into coordinated sensing, decision-making, and action across many machines at once.


The hard, unsolved part is the model that makes them act like they share one mind. That is the part you would own.


As an AI Engineer, you would architect across perception, reasoning, and control rather than picking up a slice someone else scoped. Day-to-day includes training and evaluating VLA models, building the architectures for multimodal fusion and continual learning, giving agents memory and tool use, and pushing all of it from research into real-time inference that runs onboard while the hardware is in motion. You would also be in the field for trials, watching your work hold or break under real constraints and fixing it on the spot.


They're coming off a colossal funding round but are still early enough that you will help set the culture and the process. The work is demanding and the pace is fast but the payoff is that what you build gets deployed instead of archived.


The fit: you have spent at least two years shipping AI models, ideally in robotics, agents, autonomous systems, or anything that has to work in real time. You are strong in computer vision, deep learning, or multimodal architectures such as VLMs and transformers. You understand distributed training, fine-tuning, and reinforcement learning, and you have personally carried something from prototype to product in a place that moved fast.


Non-negotiable: the role requires access to U.S. export controlled information, so you must be a U.S. Person.


On offer: meaningful equity, top-of-range salary package, fully covered medical, dental, and vision, strong PTO, relocation support where eligible, and a team pulled from the top of autonomy, AI, and national security. Backed by well-known defense and frontier investors.


If the work you most want to do is autonomy that ships to real systems and matters when it gets there, this is worth a conversation.

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