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Remote Generative Ai Engineer Jobs in Itasca, IL

The Hartford

Principal AI Engineer

Chicago, IL · On-site +1

This role can have a Hybrid or Remote work arrangement. Candidates who live near one of our office ... AI / generative AI * Experience with CI/CD pipelines, Automated Testing, Automated Deployments ...

paradigm

Principal AI Architect - Remote

Lombard, IL · Remote

We are seeking a full-time, remote Principal AI Architect. The Principal AI Architect role provides ... in enterprise software engineering, cloud architecture, AI/ML, and Generative AI, with ...

paradigm

Principal AI Architect - Remote

Lombard, IL · Remote

We are seeking a full-time, remote Principal AI Architect. The Principal AI Architect role provides ... in enterprise software engineering, cloud architecture, AI/ML, and Generative AI, with ...

Paradigm

Principal AI Architect - Remote

Lombard, IL · On-site +1

$125K - $170K/yr

We are seeking a full-time, remote Principal AI Architect.The Principal AI Architect role provides ... in enterprise software engineering, cloud architecture, AI/ML, and Generative AI, with ...

Career Renew

Senior ML Engineer

Chicago, IL · Remote

$180K - $240K/yr

Leading the exploration and application of Large Language Models and Generative AI, venturing into ... Remote-first with strong perks -- flexible vacation, paid sabbatical after 5 years, comprehensive ...

Adidev Technologies

AI/ML

Des Plaines, IL · Remote

... feature engineering, and leveraging Generative AI algorithms for novel solutions. * Lead cross ... Support, even from afar, with our remote assistance. * Regular salary reviews? You betcha! Ready to ...

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Remote Generative Ai Engineer information

See Itasca, IL salary details

$37K

$112.8K

$186.5K

How much do remote generative ai engineer jobs pay per year?

As of Aug 27, 2026, the average yearly pay for remote generative ai engineer in Itasca, IL is $112,813.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,800.00 and $147,500.00 per year, depending on experience, location, and employer.

What is a remote generative AI engineer?

A Remote Generative AI Engineer is a technology professional who specializes in developing, training, and deploying artificial intelligence models that can generate new content—such as text, images, audio, or video—while working from a remote location. These engineers typically work with advanced machine learning techniques like deep learning, neural networks, and large language models. Their responsibilities often include designing algorithms, optimizing model performance, and collaborating with distributed teams to build innovative AI-driven solutions. The remote aspect allows them to perform their duties from anywhere with internet access, offering flexibility and access to global opportunities.

What are the key skills and qualifications needed to thrive as a remote generative AI engineer?

To thrive as a Remote Generative AI Engineer, you need a solid background in computer science, machine learning, and deep learning, typically with a relevant degree and experience in building AI models. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (such as AWS or Azure), and version control systems like Git is essential. Strong problem-solving, self-motivation, and effective remote communication set outstanding engineers apart in this role. These skills are crucial for developing innovative AI solutions, collaborating across distributed teams, and delivering impactful results in a remote work environment.

How do remote generative AI engineers typically collaborate with cross-functional teams to deliver AI-driven solutions?

Remote Generative AI Engineers often work closely with data scientists, product managers, and software engineers to integrate generative AI models into products or services. Collaboration is usually facilitated through virtual meetings, code repositories, and project management tools, enabling seamless communication across different time zones. Regular check-ins and sprint reviews help ensure alignment on goals, while documentation and clear communication are essential for maintaining project momentum. This collaborative environment not only fosters innovation but also allows engineers to gain exposure to a variety of perspectives and expertise.

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

AspectRemote Generative Ai EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related; experience with generative modelsBachelor's or higher in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentCollaborates on AI model development, focuses on generative models like GPT, GANsDevelops and deploys ML models for various applications, including predictive analytics
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, and data-driven industries

While both roles involve AI and machine learning, a Remote Generative Ai Engineer specializes in creating models that generate content, such as text or images, using generative techniques. In contrast, a Remote Machine Learning Engineer works on a broader range of ML models for predictive or classification tasks. The roles often overlap but differ in focus and application.

How much does a remote generative AI engineer make?

A remote generative AI engineer typically earns between $100,000 and $160,000 annually, depending on experience, skills, and the company's location. Senior roles or those with specialized expertise in machine learning and deep learning can command higher salaries, especially with proficiency in tools like TensorFlow or PyTorch.

What are the best remote generative AI engineer jobs?

Remote generative AI engineer jobs are available across technology companies, research institutions, and startups, often requiring skills in machine learning frameworks like TensorFlow or PyTorch and experience with natural language processing or computer vision. These roles typically involve developing and deploying AI models remotely, with some positions offering flexible schedules and requiring certifications or advanced degrees in computer science or related fields.

What is the average salary of a remote generative AI engineer?

The average salary for a remote generative AI engineer typically ranges from $100,000 to $150,000 annually, depending on experience, skills in machine learning frameworks, and the complexity of projects. Senior roles or those with specialized expertise in deep learning and large language models can earn higher compensation. Remote positions often offer competitive pay comparable to on-site roles in the tech industry.

What are popular job titles related to Remote Generative Ai Engineer jobs in Itasca, IL?

For Remote Generative Ai Engineer jobs in Itasca, IL, the most frequently searched job titles are:

What job categories do people searching Remote Generative Ai Engineer jobs in Itasca, IL look for?

The top searched job categories for Remote Generative Ai Engineer jobs in Itasca, IL are:

What cities near Itasca, IL are hiring for Remote Generative Ai Engineer jobs?

Cities near Itasca, IL with the most Remote Generative Ai Engineer job openings:

Remote Generative Ai Engineer jobs near you

Forward Deployed Engineer (Generative AI)

Tiger Analytics Inc.

Chicago, IL • Remote

Full-time

Re-posted 13 days ago

Job description

Tiger Analytics is looking for experienced Forward Deployed Engineer (Generative AI) with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

Role Overview

The Forward Deployed Engineer (FDE) drives the on-site deployment, integration, and scaling of our enterprise Generative AI solutions. This role embeds directly within customer engineering teams to operationalize Large Language Models (LLMs) and retrieval systems across multi-cloud environments (AWS, Azure, GCP). You will bridge the gap between AI research and production-grade cloud infrastructure.

You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Requirements

Agentic Design & Implementation
● Develop intelligent agents using Vertex AI Agent Builder to automate complex
business workflows.
● Leverage the Agent Developer Kit (ADK) to build and manage multi-agent systems
that collaborate to solve end-to-end business challenges.
● Implement tools like MCP (Model Context Protocol) Toolbox to securely connect
agents to enterprise databases like BigQuery and Spanner.


AI on Data Strategy
● Utilize Vertex AI for model training, tuning, and deployment, ensuring seamless
integration with BigQuery for feature engineering.
● Build and optimize streaming data pipelines (e.g., via Dataflow) to execute
real-time inference using RunInference API or Vertex AI endpoints.
● Ground AI models in live business context using vector engines within BigQuery or
AlloyDB to eliminate "AI amnesia".


Operational Excellence (Soft Skills)
● Active Participation: Show up promptly for all internal and client-facing meetings.
● Transparent Communication: Provide regular, structured status updates to team
members and stakeholders regarding project milestones and technical blockers.
● Proactive Collaboration: Demonstrate the ability to ask for help when facing
technical hurdles and contribute to a collaborative troubleshooting environment.
● Consultative Approach: Navigate corporate environments to translate high-level
business goals into robust technical architectures.
Technical Qualifications
● Vertex AI Mastery: Proven experience with Model Garden, Vertex AI Pipelines, and
model evaluation.
● Data Proficiency: Advanced knowledge of SQL for BigQuery, Python for ML
engineering, and data preprocessing techniques (scaling, encoding, imputation).
● Cloud Infrastructure: Hands-on experience with Google Cloud Storage and Vertex
AI endpoints.
● Emerging Tech: Familiarity with stateful real-time processing and the latest
innovations in agentic architectures.

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

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