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Generative Ai Phd Jobs in Virginia (NOW HIRING)

... generative AI, and Agentic AI. • Experience analyzing complex data sets to identify patterns and ... PhD + 2 years of experience. • Expert/ Master: High School Diploma + 12 years of experience ...

... PhD-level research environments. • Ability to rapidly learn and apply new AI/ML methodologies ... generative AI, reinforcement learning, computer vision, or related disciplines. • Experience ...

Key Responsibilities Design and build supervised, unsupervised, and generative AI models (including ... Master's or PhD strongly preferred. Additional relevant experience may be substituted for degree ...

Key Responsibilities • Design and build supervised, unsupervised, and generative AI models ... Master's or PhD strongly preferred. Additional relevant experience may be substituted for degree ...

... PhD-level research environments. * Ability to rapidly learn and apply new AI/ML methodologies ... generative AI, reinforcement learning, computer vision, or related disciplines. * Experience ...

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Generative Ai Phd information

What is a generative AI PhD?

A Generative AI PhD is a doctoral program focused on researching and developing artificial intelligence systems that can generate new content, such as text, images, music, or code. Students in this program study advanced machine learning techniques, including deep learning, neural networks, and probabilistic models. The goal is to push the boundaries of what AI can create, leading to innovations in fields like natural language processing, computer vision, and creative arts. Graduates often pursue careers in academia, research labs, or tech companies working on cutting-edge AI technologies.

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

To thrive as a Generative AI PhD, you need deep expertise in machine learning, mathematics, and computer science, typically supported by a doctoral degree in a related field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and experience with large-scale data and cloud computing are essential. Strong research acumen, critical thinking, and the ability to clearly communicate complex ideas are vital soft skills for success in academic or industry settings. These skills drive innovative research, enable effective collaboration, and ensure impactful contributions to the rapidly evolving field of generative AI.

What are some common challenges faced when transitioning from academic research to an industry role as a generative AI PhD?

One common challenge is adapting to faster-paced project timelines, as industry work often emphasizes practical results and product integration over long-term theoretical exploration. Additionally, collaboration across multidisciplinary teams—including software engineers, product managers, and designers—requires strong communication skills to translate complex research into actionable solutions. Many new hires also find it necessary to balance advancing the state-of-the-art with addressing immediate business needs, which can shift the focus from pure research to more applied problem-solving.

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

AspectGenerative Ai PhdMachine Learning Engineer
Required CredentialsPhD in AI, Computer Science, or related fieldBachelor's or Master's in CS, AI, or related field
Work EnvironmentResearch labs, academia, R&D departmentsTech companies, startups, industry projects
Employer & Industry UsageAcademic institutions, research firms, AI labsTech firms, software companies, AI product teams

Generative Ai Phds focus on advanced research, developing new models and theories in AI, often working in academic or research settings. Machine Learning Engineers implement AI models into products, working in industry environments to develop scalable solutions. While both roles require strong AI knowledge, the PhD emphasizes research depth, whereas the Engineer emphasizes application and deployment.

What are popular job titles related to Generative Ai Phd jobs in Virginia?

For Generative Ai Phd jobs in Virginia, the most frequently searched job titles are:

What cities in Virginia are hiring for Generative Ai Phd jobs?

Cities in Virginia with the most Generative Ai Phd job openings:

Infographic showing various Generative Ai Phd job openings in Virginia as of August 2026, with employment types broken down into 71% Full Time, 27% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Data Scientist - NLP / Generative AI

AIToolboard

Arlington, VA • On-site

$150 - $190/hr

Other

Medical, Dental, Vision, Retirement

Posted 15 days ago


Job description

Jobs / Data Scientist - NLP / Generative AI

Data Scientist - NLP / Generative AI

Full-time

About the Role

Data Scientist – NLP / Generative AILocation: Hybrid – Arlington, VirginiaEmployment Type: Full-timeBizFirst is assisting our client with the hiring of a Data Scientist specializing in natural language processing and generative AI to help the organization move from early experimentation into production-ready AI capabilities. This is a hands-on research and engineering role where you will own the design and delivery of NLP and GenAI solutions applied directly to the client’s most complex internal workflows.Our client is a mid-market professional services organization that is actively rethinking how it designs and executes its core business operations through artificial intelligence and automation. The company is building a dedicated AI capability to embed machine learning and generative AI into its most critical internal workflows – from decision support and process automation to real-time analytics and intelligent document processing.What will you doThe ideal candidate brings 5–8 years of applied data science experience with a deep specialization in NLP and a working command of modern generative AI techniques. You have built production NLP systems, worked with transformer-based architectures, and have direct experience with large language models – including fine-tuning, prompt engineering, and retrieval-augmented generation (RAG). You are comfortable moving between research and engineering as the work demands.

Responsibilities
  • Design and build NLP and generative AI solutions applied to internal business processes, including document understanding, classification, summarization, and conversational AI.
  • Develop, fine-tune, and evaluate large language models and transformer-based architectures for domain-specific applications.
  • Build and iterate on retrieval-augmented generation (RAG) systems, embedding pipelines, and vector search infrastructure.
  • Work closely with business and operations stakeholders to scope problems, define evaluation criteria, and validate model outputs against real-world requirements.
  • Analyze and interpret model behavior, identify failure modes, and develop mitigation strategies to ensure reliable, responsible outputs.
  • Collaborate with ML engineers and platform teams to move experiments into production pipelines.
  • Document experimental methodology, data lineage, and model evaluations to support reproducibility and knowledge sharing.
  • Stay current on developments in NLP research and GenAI tooling, bringing relevant advances into the team’s work quickly.
Requirements
  • US Citizen or Permanent Resident authorized to work in the United States.
  • Experience: 5–8 years of applied data science experience with a strong focus on natural language processing and text-based systems.
  • NLP & GenAI: Hands-on experience with transformer architectures (BERT, GPT, T5, or similar), fine-tuning workflows, and production deployment of language models.
  • RAG & Embeddings: Direct experience building retrieval-augmented generation pipelines, vector databases (Pinecone, Weaviate, FAISS, or equivalent), and semantic search systems.
  • Programming: Strong Python skills; proficiency with HuggingFace Transformers, LangChain, or similar GenAI tooling.
  • Evaluation: Experience designing rigorous evaluation frameworks for generative models, including human evaluation, LLM-as-judge approaches, and automated benchmarking.
  • Preferred: Experience applying NLP in a professional services, legal, finance, or consulting domain.
  • Familiarity with responsible AI practices, including bias assessment, output auditing, and hallucination mitigation.
  • Background in information extraction, named entity recognition (NER), or document intelligence.
  • Experience with cloud-based GenAI services (OpenAI API, Anthropic API, AWS Bedrock, Azure OpenAI, or GCP Vertex AI).
  • Graduate degree (MS or PhD) in Computer Science, Computational Linguistics, Statistics, or a related field.
Benefits
  • Family Health Care (54% cost covered for the entire family)
  • Family Dental (54% cost covered for the entire family)
  • Family Vision (54% cost covered for the entire family)
  • Flexible Spending Account
  • Performance bonuses tied to project and delivery milestones
  • Lifetime Event Bonuses (e.g., new child, marriage)
  • Profit-sharing arrangement for any work brought into the company
  • Unlimited Leave with Approval
  • 401k – 100% employer match on first 4% invested
  • $1,500 annual training and conference budget

Job Type: Full-time, Permanent Position

Work Authorization:US Citizen or Permanent Resident; no active security clearance required.

Schedule:Monday to Friday

Work Location:Hybrid – Arlington, Virginia

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