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Generative Ai Researcher Jobs in Arizona (NOW HIRING)

AI Engineer

Phoenix, AZ ยท On-site

$120 - $160/hr

Stay up to date on the latest advancements in generative AI research and actively contribute to the continuous improvement of our AI capabilities. Champion responsible AI development practices ...

Leverages generative AI and emerging technologies in compliance with firm policies to enhance research quality and efficiency. * Continuously evaluates new tools, databases, and resources to improve ...

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Generative Ai Researcher information

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 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 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.

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 popular job titles related to Generative Ai Researcher jobs in Arizona?

For Generative Ai Researcher jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Generative Ai Researcher jobs in Arizona look for?

The top searched job categories for Generative Ai Researcher jobs in Arizona are:

What cities in Arizona are hiring for Generative Ai Researcher jobs?

Cities in Arizona with the most Generative Ai Researcher job openings:

Data Scientist, Principal - AI Product Engineering (Phoenix)

Phoenix, AZ โ€ข On-site

Full-time

Posted 8 days ago


Job description

Your Role

The AI & Machine Learning team works in partnership across the enterprise to accelerate business outcomes by applying AI, machine learning, and generative AI to build intelligent products that create intelligence at scale. Reporting to the Director, AI & Machine Learning, the Data Scientist, Principal will lead the development and deployment of novel applications that leverage generative AI models. This role focuses on rapidly developing new features and working across partner teams to deliver solutions and maximize impact, translating cutting-edge AI research into real-world products and taking features from 0 to 1. You will design, build, and ship production-grade AI products including LLM-powered applications, AI agents and copilots, retrieval-augmented generation (RAG) and search, and AI-enabled automation embedded directly into customer-facing applications and enterprise workflows such as claims, payment integrity, clinical insights, and member experience. You will set the technical direction for how AI is applied across the organization.

Our leadership model is about developing great leaders at all levels and creating opportunities for our people to grow - personally, professionally, and financially. We are looking for leaders that are energized by creative and critical thinking, building and sustaining high-performing teams, getting results the right way, and fostering continuous learning.

Your Knowledge and Experience
  • Bachelor's degree in computer science, a quantitative discipline, or equivalent practical experience; Master's degree or PhD preferred
  • 10 years of prior relevant experience in data science, machine learning, applied AI/ML, software engineering, or advanced analytics
  • Proven track record of building and shipping software products rapidly, not just developing models or analyses
  • Strong software engineering skills and proficiency in Python, including building APIs and backend services
  • Experience leading ML design and optimizing ML infrastructure, model deployment, evaluation, and data processing, and working with machine learning frameworks and libraries
  • Hands-on experience with deep learning and LLM application frameworks, including PyTorch, TensorFlow, LangChain, and LangGraph
  • Hands-on experience building applications that leverage generative AI models, including prompt engineering and retrieval-augmented generation (RAG)
  • Experience with generative AI research or applications preferred
  • Experience designing agent-based systems and orchestration frameworks preferred
  • Experience with cloud computing platforms and infrastructure (e.g., Azure, Google Cloud, or AWS), and scalable data processing with SQL or Spark preferred
  • Solid MLOps and LLMOps practices, including CI/CD, monitoring, and model lifecycle management preferred
  • Experience rapidly developing and shipping software in a fast-paced, customer-facing environment, adapting to changing priorities preferred
  • Understanding of responsible AI and governance for regulated or healthcare environments preferred
Hybrid

This role requires employees to be in-office based on our hybrid workplace model, balancing purposeful in-person collaboration with flexibility. For most teams, this means coming into the office two days each week.

Employees living more than 50 miles from an office location will work with their manager to determine in-office time based on business need.

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