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Generative Ai Chatbot Jobs in Washington (NOW HIRING)

Experience building feature repositories for AI-ML model trainingProject work in deep learning, transformers, computer vision, NLP, or chatbot developmentExperience in developing Generative AI ...

AI/ML Subject Matter Expert

Vienna, VA · On-site

$195K - $210K/yr

Project work in deep learning, transformers, computer vision, NLP, or chatbot development * Experience in developing Generative AI applications especially using LLMs in domains such as NLP and image ...

AI Engineer

Washington, DC · On-site

$99 - $225/hr

... Generative AI applications using LLMs, RAG frameworks, and vector stores Experience designing and ... Experience with end-to-end chatbot or agent to agent (A2A) development * Experience with enterprise ...

They are developing generative AI regulatory specific chatbot similar to a chatGPT. * Called "FILLIP" - platform can process long documents * Complexity - lots of things can break * Someone ...

Leverage GenAI to build chatbot integrated with RAG, MCP servers, context engineering and momery ... such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work. Visa ...

Showing results 21-29

Generative Ai Chatbot information

What is a generative AI chatbot?

A Generative AI Chatbot is an artificial intelligence system designed to engage in human-like conversations by generating responses to user inputs in real time. Unlike traditional rule-based chatbots that rely on predefined scripts, generative AI chatbots use advanced machine learning models—often based on large language models—to understand context and produce original, relevant responses. These chatbots can be used in customer service, education, entertainment, and more, offering personalized and dynamic interactions. They continue to improve as they process more data and user interactions.

What are some common challenges faced by professionals working on generative AI chatbot development, and how can they be addressed?

Professionals developing generative AI chatbots often encounter challenges such as managing ambiguous user inputs, ensuring conversational relevance, and maintaining ethical standards like avoiding biased or inappropriate responses. Collaboration with interdisciplinary teams—including data scientists, linguists, and UX designers—is vital to continuously improve the chatbot's performance. Regular testing, user feedback, and fine-tuning of language models are essential practices to address these challenges and enhance the chatbot's ability to handle diverse real-world conversations.

What are the key skills and qualifications needed to thrive as a generative AI chatbot developer, and why are they important?

To thrive as a Generative AI Chatbot Developer, you need strong programming expertise (especially in Python), a solid understanding of machine learning and natural language processing (NLP), and typically a degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with APIs, and knowledge of cloud platforms such as AWS or Azure are commonly required, along with relevant AI or ML certifications. Creativity, problem-solving, and effective communication are vital soft skills for designing engaging, user-friendly conversational experiences and collaborating with cross-functional teams. These skills are crucial for building reliable, scalable, and innovative AI chatbots that meet user needs and business objectives.

What is the difference between Generative Ai Chatbot vs Data Scientist?

AspectGenerative Ai ChatbotData Scientist
Required CredentialsBasic programming, AI/ML knowledgeDegree in Data Science, Statistics, or related field
Work EnvironmentTech companies, customer service platformsResearch labs, corporate analytics teams
Industry UsageAutomated customer interactions, content generationData analysis, predictive modeling, insights
Search & Comparison IntentUnderstanding AI chatbot capabilitiesData analysis skills and roles

Generative Ai Chatbots focus on creating conversational AI for customer engagement, requiring programming and AI knowledge. Data Scientists analyze data to generate insights, often with advanced degrees. While both work in tech environments, their roles differ in purpose and skill set.

What job categories do people searching Generative Ai Chatbot jobs in Washington look for?

The top searched job categories for Generative Ai Chatbot jobs in Washington are:

What cities in Washington are hiring for Generative Ai Chatbot jobs?

Cities in Washington with the most Generative Ai Chatbot job openings:

Infographic showing various Generative Ai Chatbot job openings in Washington as of August 2026, with employment types broken down into 81% Full Time, 16% Part Time, and 3% Contract. Highlights an 59% Physical, 3% Hybrid, and 38% Remote job distribution.

AI/ML Subject Matter Expert

Halvik

Vienna, VA • Remote

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted yesterday


Job description

Halvik Corp delivers a wide range of services to 13 executive agencies and 15 independent agencies. Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning, Cyber Security and Cutting-Edge Technology across the US Government. Be a part of something special!Responsibilities:Responsible for developing and implementing AI/ML solutions to solve complex problems and enhance business operations.Define direction of mission-critical solutions using best-fit AI/ML algorithms and technologiesWork closely with cross-functional teams to design, develop, and deploy AI models and algorithms that enable data-driven decision making.Conduct statistical analyses using ML techniques for customer-focused solutionsCollaborate with cross-functional teams to deliver world-class solutions for large-scale data processingGuide clients in navigating ML algorithms, tools, and frameworksDesign, develop, and deploy AI models for data-driven decision making and business innovationCreate intelligent systems that automate processes, improve efficiency, and drive business innovation, leveraging their expertise in AL/ML, deep learning, and data analysis.Create, train, and maintain intelligent systems to automate processes and improve efficiencyReport on industry trends and recommend solutions for AI/ML integrationDesign and build ML models solving real-world business problemsMake informed ML infrastructure decisions based on modeling techniques and issuesWrite and test application code, develop ML models, and automate tests and deploymentRetrain, maintain, and monitor production modelsLeverage cloud-based architectures to deliver optimized ML models at scaleConstruct optimized data pipelines for ML modelsImplement CI/CD best practices for ML model and application code deploymentEnsure code security, model governance, and adherence to Responsible and Explainable AI practicesRegularly recommend and report on industry trends and solutions to meet evolving client needs regarding techniques, tools and technologies for AI/ML integration. Requirements:Master's degree or Bachelor's of science with 5+ years of industry experience in Computer Science, Software Engineering, Data Science, Statistics, or related STEM field.5+ years of experience in AI, data science, ML engineering, or related fields4+ years of experience with modern cloud computing technologies (AWS, Databricks, Microsoft Azure or GCP)Experience in fine-tuning LLMs for custom datasets and/or using RAG to augment LLM applications.Knowledge of multiple ways of tackling AI/ML problems and demonstrated ability to make good initial choices to make systems that perform well more quicklyExperience using Generative AI tools to help in software programming and testing (e.g. VS-Code or GitHub with copilot AI)Proficiency in SQL, including advanced query techniquesExperience with version control systems (e.g., Git, Github, Jenkins)6+ years of proficiency in Python and Jupyter notebooks. Experience with other languages such as R, and Scala is a plus but not necessary.Experience developing and assessing AI/ML models and ensemblesSupport the seamless integration of multi-media data processing into platform data pipelinesExperienced in planning, setting-up, running and reporting on AI/ML experiments.Experience building feature repositories for AI-ML model trainingProject work in deep learning, transformers, computer vision, NLP, or chatbot developmentExperience in developing Generative AI applications especially using LLMs in domains such as NLP and image processingKnowledge of modern software design patterns (e.g., microservices, edge computing)Experience working with LLM frameworks and foundation models like LLaMa-3 and experience working with LLM model repositories like HuggingfaceFamiliarity with MLOps practices and tools for model versioning and experiment trackingExperience identifying appropriate AI/ML models for a problem and using appropriate techniques to evaluate performance to choose the best modelExperience with techniques for tuning model parameters to application data and conditions Abilities:Ability to lead an Agile team of data scientists, engineers, architects and testersDemonstrated ability to work independentlyStrong problem-solving skills and ability to think creatively to overcome technical challengesParticipate in the full machine learning lifecycle, from business understanding, data collection and preprocessing to model selection, evaluation, deployment and monitoringAdapt to rapidly changing technologies and methodologies in the AI/ML fieldExcellent communication, analytical, and interpersonal skillsAbility to gather requirements and work effectively as part of an Agile teamCapacity to explain complex technical concepts to non-technical stakeholdersExcellent technical writing skillsCollaborate with business stakeholders to identify opportunities for AI/ML applicationsDevelop and maintain documentation for ML models, including methodology, assumptions, and limitationsMentor junior team members and contribute to the growth of the AI/ML practiceAbility to thrive in a mainly remote work environmentCommitment to continuous learning in the fast-evolving AI/ML landscape and look for ways to apply new techniques when appropriate.Desired Qualifications:Having experience and a good understanding of Ux, Human-AI teaming, human factors in AI and software systemsPublished research papers or patents in the field of AI/MLKnowledge of Agentic AI Systems (e.g. AutoGen, LangGraph, LangChain, CrewAI etc.)Experience with Knowledge Graphs tools and techniquesExperience with federated learning or privacy-preserving machine learning techniquesKnowledge of data visualization techniques and toolsGPU programming experiencePrivacy Policy – Halvik CorpHalvik offers a competitive full benefits package including:Company-supported medical, dental, vision, life, STD, and LTD insuranceBenefits include 11 federal holidays and PTOEligible employees may receive performance-based incentives in recognition of individual and/or team achievements.401(k) with company matchingFlexible Spending Accounts for commuter, medical, and dependent care expensesTuition AssistanceCharitable Contribution matchingHalvik Corp is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.Halvik's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.