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Generative Ai Scientist Jobs (NOW HIRING)

Saransh Inc

AI/ML Architect

Irvine, CA · On-site

$68.50 - $88/hr

LLM & Generative AI Development * Agent-Based Systems * Retrieval-Augmented Systems (RAG) * Enterprise AI Integration * AI/ML, Data Science, AI Architecture, Python, LLM, CI/CD Must Have Skills:

Ascend Learning

Sr Data & AI Scientist

Leawood, KS · On-site +1

$151K - $215K/yr

WHAT YOU'LL DO The Senior Data and AI Scientist leads strategic data science and AI initiatives ... Specialized knowledge of generative AI and large language model tooling and frameworks (e.g ...

Kai

Principal Applied AI Scientist

San Jose, CA · On-site

$200 - $250/hr

We are looking for a Principal Applied AI Scientist to lead the design and deployment of cutting‑edge Generative AI and LLM‑powered systems for real‑world, high‑impact applications. This is a ...

Forhyre

Generative AI Strategist

New York, NY

$132K - $171K/yr

Work closely with various teams within the customer's organization, including applied scientists ... Proven experience in strategizing and implementing generative AI solutions in a business context.

OVA.Work

Applied AI Scientist

... generative AI technologies. • Design and implement Retrieval-Augmented Generation (RAG), AI ... D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics ...

Forhyre

$108K - $139K/yr

Work closely with various teams within the customer's organization, including applied scientists ... Proven experience in strategizing and implementing generative AI solutions in a business context.

Forhyre

$119K - $154K/yr

Work closely with various teams within the customer's organization, including applied scientists ... Proven experience in strategizing and implementing generative AI solutions in a business context.

Forhyre

Generative AI Strategist

New York, NY · On-site

$132K - $171K/yr

Work closely with various teams within the customer's organization, including applied scientists ... Proven experience in strategizing and implementing generative AI solutions in a business context.

Forhyre

Generative AI Strategist

Plano, TX

$116K - $150K/yr

Work closely with various teams within the customer's organization, including applied scientists ... Proven experience in strategizing and implementing generative AI solutions in a business context.

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All JobsGenerative Ai Scientist Jobs

Generative Ai Scientist information

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$37.5K

$122.7K

$196.5K

How much do generative ai scientist jobs pay per year?

As of Sep 9, 2026, the average yearly pay for generative ai scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

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

AspectGenerative Ai ScientistMachine Learning Engineer
Required CredentialsAdvanced degrees in AI, Computer Science, or related fields; expertise in deep learning and generative modelsDegree in CS, Data Science, or related; strong programming and ML knowledge
Work EnvironmentResearch labs, AI startups, tech companies focusing on AI innovationTech companies, startups, or enterprise environments implementing ML solutions
Employer & Industry UsagePrimarily in AI research, product development involving generative modelsDeveloping and deploying ML models for various applications across industries

Generative Ai Scientists focus on creating and improving generative models like GANs and VAEs, often working in research settings. Machine Learning Engineers implement and optimize ML models for practical applications. While both roles require strong AI knowledge, Generative Ai Scientists are more research-oriented, whereas Machine Learning Engineers focus on deployment and integration.

How to become a generative AI scientist?

To become a generative AI scientist, one typically needs a strong background in computer science, machine learning, and deep learning, often with a master's or Ph.D. in a related field. Gaining experience with neural networks, programming in Python, and working with frameworks like TensorFlow or PyTorch is essential, along with staying updated on the latest research and techniques in generative models such as GANs and VAEs.

What does a generative AI scientist do?

A generative AI scientist develops algorithms and models that create new data, such as images, text, or audio, using techniques like deep learning and neural networks. They often work with large datasets, programming languages like Python, and machine learning frameworks to improve AI's ability to generate realistic and useful content.

What are popular job titles related to Generative Ai Scientist jobs?

For Generative Ai Scientist jobs, the most frequently searched job titles are:

Infographic showing various Generative Ai Scientist job openings in the United States as of September 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% In-person job distribution, with an average salary of $122,738 per year, or $59 per hour.

AI/ML Architect

Irvine, CA • On-site

Saransh Inc
IT Services • 51 - 200 employees
Learn more about Saransh Incexternal

$68.50 - $88/hr

Contractor

Re-posted 23 days ago

Job description

Role: AI Scientist / AI Architect
Location: 4 days a week onsite is must (3 days in Irvine, CA & 1 Day in Downtown, LA, CA)
Job Type: Contract
Description:
  • A highly skilled hands-on AI Scientist / Architect with at least 8+ years of experience in AI/ML, Data Science, or Software Engineering.
  • You bring strong expertise in designing and building scalable, production-ready AI solutions, with deep hands-on experience in LLM-enabled applications, agent-based systems, and cloud-native architectures.
  • You are comfortable working closely with business stakeholders and leading AI-driven innovation initiatives in an enterprise environment.
Note:
Mandatory Areas:
  • AI/ML Solution Architecture
  • LLM & Generative AI Development
  • Agent-Based Systems
  • Retrieval-Augmented Systems (RAG)
  • Enterprise AI Integration
  • AI/ML, Data Science, AI Architecture, Python, LLM, CI/CD
Must Have Skills:
• Python & Backend Development
• LLM / Generative AI Application Development
• Agent-Based AI Systems
• RAG / Vector DB / Embeddings
• API Development & System Integration
• AWS Cloud (Cloud-Native Development)
• CI/CD & DevOps Practices
• Observability (Logging, Monitoring, Tracing)
Responsibilities:
  • Design and develop scalable AI/ML pipelines and intelligent applications aligned with enterprise standards
  • Build agent-based AI workflows, automation systems, and retrieval-based architectures (RAG, vector search, embeddings)
  • Architect and implement LLM orchestration layers supporting content ideation, drafting, and editing workflows
  • Lead integration of AI solutions with backend systems and enterprise platforms (APIs, internal tools, data platforms)
  • Partner with product, marketing, and business stakeholders to translate requirements into AI-driven solutions
  • Provide architectural leadership, guide offshore teams, and ensure delivery aligned with scalability, security, and governance standards.
Requirements:
  • At least 8+ years of experience in AI/ML, Data Science, or Software Engineering
  • Strong Python backend development experience
  • Hands-on experience with LLM-enabled applications and Generative AI
  • Experience building agent-based / agent-oriented AI systems
  • Strong expertise in retrieval-based systems (RAG, vector databases, embeddings, indexing)
  • Experience with API development and backend system integration.
  • AWS cloud-native development experience
  • Experience with CI/CD pipelines and environment management
  • Strong understanding of observability (logging, monitoring, tracing)
  • Experience deploying ML models in production environments
  • Exposure to enterprise AI workflows, automation, and governance models.
Domain Experience (If any):
• AI-enabled enterprise workflows
• Marketing / Content generation platforms (nice to have)
• Financial / Investment domain (preferred based on content use cases)
Certifications:
• Not mandatory (AWS / ML / AI certifications are good to have)