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Generative Ai Researcher Jobs (NOW HIRING)

Hum AI

AI Researcher

San Francisco, CA · On-site

AI Researcher Location: San Francisco About Hum.ai Hum.ai is building planetary superintelligence ... Join us at the cutting edge, where we're scaling generative transformer diffusion models, designing ...

Cisco

AI Researcher Hybrid

San Jose, CA · On-site

Meet the Team Join Cisco's Enterprise AI team, the core group enabling Generative AI powered ... Serves as research strategy liaison to engineers and product managers and works collaboratively ...

Cisco

AI Researcher Hybrid

San Jose, CA · On-site

Meet the Team Join Cisco's Enterprise AI team, the core group enabling Generative AI powered ... Serves as research strategy liaison to engineers and product managers and works collaboratively ...

Visa

Head of Generative AI Research

Foster City, CA · On-site

As Head of Generative AI Research, you will shape Visa's GenAI research agenda, collaborate with top academic institutions, publish in premier AI conferences, and work closely with product and ...

Visa

Head of Generative AI Research

Foster City, CA · Hybrid

As Head of Generative AI Research, you will shape Visa's GenAI research agenda, collaborate with top academic institutions, publish in premier AI conferences, and work closely with product and ...

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All JobsGenerative Ai Researcher Jobs

Generative Ai Researcher information

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$30K

$113.1K

$164.5K

How much do generative ai researcher jobs pay per year?

As of Jun 18, 2026, the average yearly pay for generative ai researcher in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What are some common challenges Generative AI Researchers face when transitioning models from research to production environments?

Generative AI Researchers often encounter challenges when moving models from experimental research settings into real-world production. These challenges include ensuring models are robust to diverse, unseen data, optimizing for computational efficiency, and addressing potential biases or ethical concerns present in generated outputs. Collaboration with engineering teams is key to deploying scalable solutions, while ongoing monitoring is necessary to maintain model performance and compliance. Researchers should be prepared to iterate on their models post-deployment based on feedback and real-world results.

What does a Generative AI Researcher do?

A Generative AI Researcher studies and develops artificial intelligence models that can create new content such as text, images, music, or code. They work on advancing algorithms like generative adversarial networks (GANs), variational autoencoders (VAEs), and large language models to improve their performance and applications. Their work often involves designing experiments, analyzing data, publishing research, and collaborating with other scientists and engineers to push the boundaries of AI creativity and utility.

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

AspectGenerative Ai ResearcherMachine Learning Engineer
CredentialsAdvanced degrees in AI, Computer Science, or related fields; research experienceDegree in Computer Science, Data Science, or related fields; coding skills
Work EnvironmentResearch labs, academia, R&D departmentsTech companies, startups, product teams
Industry UsageFocus on developing generative models like GANs, VAEs, transformersImplementing ML models for various applications, including generative tasks

While both roles involve AI and machine learning, Generative Ai Researchers primarily focus on developing new generative models and advancing AI research, often working in academic or research settings. Machine Learning Engineers typically implement and deploy ML models in production environments across industries. The roles overlap in skills and tools but differ in their core focus and work environment.

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

To thrive as a Generative AI Researcher, you need a strong background in computer science, mathematics, and machine learning, typically supported by an advanced degree (Master's or PhD) in a relevant field. Proficiency in programming languages such as Python, experience with deep learning frameworks like TensorFlow or PyTorch, and familiarity with research tools and publication processes are essential. Creative problem-solving, critical thinking, and effective collaboration skills help researchers innovate and communicate complex ideas. These skills and qualities are crucial for advancing AI technologies, publishing impactful research, and driving progress in this rapidly evolving field.
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Generative Ai Researcher jobs near you
Infographic showing various Generative Ai Researcher job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 75% In-person, and 25% Hybrid job distribution, with an average salary of $113,102 per year, or $54.4 per hour.
Generative AI Researcher

Generative AI Researcher

Tata Consultancy Services

Warren, MI

Full-time

Posted 28 days ago

Tata Consultancy Services rating

6.5

Company rating: 6.5 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

154th of 204 rated it services

Job description

Job Summary:

We are seeking a highly skilled and creative Entry Level - Generative AI Engineer to apply state-of-the-art generative models to solve complex challenges in automotive engineering. This role focuses on creating intelligent agents that leverage generative capabilities for reasoning, planning, and executing complex tasks autonomously. The ideal candidate will bridge the gap between generative AI's creative potential and agentic AI's autonomous action, developing systems that can understand, reason, and act in dynamic environments.

Key Responsibilities

Integrated AI System Development:

Design and build AI agents that utilize large language models for reasoning and decision-making

Develop systems where generative AI components enable sophisticated planning and problem-solving

Create autonomous agents capable of using tools, APIs, and external systems through generative interfaces

Implement multi-agent systems where generative AI facilitates communication and collaboration

Generative AI Capabilities:

Fine-tune and optimize large language models for specific agentic tasks

Develop prompt engineering strategies for complex reasoning and chain-of-thought processes

Implement RAG (Retrieval-Augmented Generation) systems to enhance agent knowledge and context

Create generative models for code generation, content creation, and strategic planning within agent frameworks

Agent Architecture & Autonomy:

Build reflective agents that can critique and improve their own reasoning processes

Design goal-oriented systems that use generative AI for planning and adaptation

Implement memory architectures that allow agents to learn from experience and maintain context

Develop safety mechanisms and oversight for autonomous generative agents

Multi-Modal Agent Systems:

Integrate vision, language, and action capabilities within agent frameworks

Develop agents that can process and generate across multiple modalities (text, image, audio)

Create embodied agents that interact with digital and physical environments

Research & Innovation: Stay current with the latest academic research and open-source advancements in generative AI. Prototype new ideas and conduct experiments to validate their feasibility and impact.

Education: Ph.D in Computer Science, Electrical Engineering, Mechanical Engineering or related streams.

Technical Proficiency:

Experience with generative AI (LLMs, diffusion models, generative architectures)

Experience with agentic AI systems, reinforcement learning, or autonomous systems

Strong programming skills in Python and experience with AI/ML frameworks (PyTorch, TensorFlow)

Experience with LangChain, AutoGPT, Microsoft Autogen, or similar agent frameworks

Proficiency with transformer architectures and fine-tuning techniques

Deep understanding of prompt engineering, reasoning techniques, and LLM capabilities

Experience with RAG systems, vector databases, and knowledge retrieval

Knowledge of reinforcement learning, planning algorithms, and decision-making systems

Familiarity with multi-agent systems and emergent behavior

Ph.D

What Tata Consultancy Services employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Tata Consultancy Services

Sourced by ZipRecruiter

Tata Consultancy Services is an IT services, consulting and business solutions organization that delivers real results to global business, ensuring a level of certainty no other firm can match. TCS offers a consulting-led, integrated portfolio of IT, BPO, infrastructure, engineering, and assurance services. This is delivered through its unique Global Network Delivery Model™, recognized as the benchmark of excellence in software development. TCS delivers a level of certainty that no other firm can match--to our clients and to our employees. Come join us and experience certainty in your career. TCS a global Consulting and IT Services firm that is ranked in the top quartile by industry analysts. Our 2021 fiscal revenues topped $25 B and our market capitalization is over $170+B, yet we have a deep and large history of philanthropy and corporate social responsibility. Now approaching 600K of the best IT professionals and consultants, we are a trusted advisor, guiding our clients' enterprises through growth and transformation journeys - helping them to become agile, intelligent, automated and on the cloud. We are devoted to DEI and are recognized as a top employer and place to work.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Edison, NJ, US

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