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Remote Generative Ai Engineer Jobs (NOW HIRING)

Senior Generative AI Engineer

Potomac, MD · On-site +1

$57.25 - $73.75/hr

Our client is seeking a Senior Generative AI Engineer to drive internal initiatives and provide AI ... Remote location but greater Washington, DC area preferred for hybrid engagement * Sponsored AWS ...

Senior Generative AI Engineer

Washington, DC · On-site +1

$62.50 - $80.75/hr

Our client is seeking a Senior Generative AI Engineer to drive internal initiatives and provide AI ... Remote location but greater Washington, DC area preferred for hybrid engagement * Sponsored AWS ...

Senior Generative AI Engineer

Potomac, MD · Remote

$56.50 - $73/hr

Our client is seeking a Senior Generative AI Engineer to drive internal initiatives and provide AI ... Remote location but greater Washington, DC area preferred for hybrid engagement * Sponsored AWS ...

As a Generative AI Engineer on the ED&A team, you will build the agentic AI systems that change how Dataiku runs internally. The role is hands-on and end-to-end: you'll work close to the business ...

As a Generative AI Engineer on the ED&A team, you will build the agentic AI systems that change how Dataiku runs internally. The role is hands-on and end-to-end: you'll work close to the business ...

As a Generative AI Engineer on the ED&A team, you will build the agentic AI systems that change how Dataiku runs internally. The role is hands-on and end-to-end: you'll work close to the business ...

You will work closely with product, engineering, and data teams to design intelligent systems ... This is an exciting opportunity for someone passionate about machine learning, generative AI, LLMs ...

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

As of Jun 10, 2026, the average yearly pay for remote generative ai engineer in the United States is $115,864.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,000.00 and $151,500.00 per year, depending on experience, location, and employer.

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.

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

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 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.
More about Remote Generative Ai Engineer jobs
What cities are hiring for Remote Generative Ai Engineer jobs? Cities with the most Remote Generative Ai Engineer job openings:
What are the most commonly searched types of Generative Ai Engineer jobs? The most popular types of Generative Ai Engineer jobs are:
What states have the most Remote Generative Ai Engineer jobs? States with the most job openings for Remote Generative Ai Engineer jobs include:
Infographic showing various Remote Generative Ai Engineer job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $115,864 per year, or $55.7 per hour.

Generative AI Engineer (Instructor)

Sizanid Staffing

New York, NY • Remote

Part-time

Posted 22 days ago


Job description

Position: Generative AI Engineer (Instructor)

About Our Client:

Our client, a forward-thinking technology organization, is seeking an experienced Generative AI Engineer to join their team as an Instructor. This role involves not only developing innovative generative AI models and solutions but also training and mentoring teams or clients on the implementation and best practices of generative AI technologies.

Key Responsibilities:
  • Design, develop, and implement generative AI models and applications using state-of-the-art techniques.
  • Deliver training sessions, workshops, and tutorials on generative AI concepts, tools, and best practices to engineers, data scientists, and other stakeholders.
  • Create comprehensive instructional materials, including manuals, slide decks, and hands-on exercises.
  • Stay current with latest research and advancements in generative AI, NLP, and related technologies.
  • Collaborate with cross-functional teams to integrate generative AI solutions into product pipelines.
  • Provide technical guidance and support to teams adopting generative AI technology.
  • Evaluate and optimize existing AI models for performance, scalability, and robustness.
  • Assist in curriculum development for internal training programs related to AI and machine learning.

Requirements

Qualifications & Skills:

  • Advanced degree (Master’s or PhD) in Computer Science, Artificial Intelligence, Machine Learning, or related fields.
  • Bachelors with more 6-8 years experience
  • Proven experience in developing generative AI models using frameworks such as TensorFlow, PyTorch, or similar.
  • Strong knowledge of NLP techniques, transformer architectures (e.g., GPT, BERT), and generative modeling.
  • Experience in instructional design and delivering technical training or workshops.
  • Proficiency in programming languages like Python and relevant AI/ML libraries.
  • Excellent communication and presentation skills, with ability to convey complex technical concepts to diverse audiences.
  • Familiarity with cloud AI platforms (AWS SageMaker, Google AI Platform, Azure ML) is a plus.

Preferred Qualifications:

  • Experience with prompt engineering and fine-tuning large language models.
  • Background in developing AI products or solutions in a commercial environment.
  • Strong teamwork and mentoring abilities.
  • Active contributor to AI research or open-source projects.

Benefits

Part time. Pay depends on experience.