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Ai Lab Jobs in Washington (NOW HIRING)

System One

Senior Data Scientist (AI)

Washington, DC · Remote

The AI Lab operates as a small, agile team where practitioners are expected to move between research, development, and deployment activities. This position will contribute to strategy while doing ...

System One

Senior Data Scientist (AI)

Washington, DC · Remote

The AI Lab operates as a small, agile team where practitioners are expected to move between research, development, and deployment activities. This position will contribute to strategy while doing ...

System One

Senior Data Scientist (AI)

Washington, DC · Remote

The AI Lab operates as a small, agile team where practitioners are expected to move between research, development, and deployment activities. This position will contribute to strategy while doing ...

Sparks Group

Senior Business Analyst

Washington, DC · On-site

$50 - $60/hr

Our client is establishing an AI Lab, and they are looking for a Senior Business Analyst to support the AI Lab Director by anchoring the lab's requirements gathering, project coordination, governance ...

Sparks Group

Senior Data Scientist

Washington, DC · On-site

$70 - $81/hr

Our client is establishing an AI Lab to explore and implement generative AI and machine learning solutions that enhance staff productivity, improve analytical capabilities, and strengthen their ...

Carlyle

Enterprise AI Product Manager

Washington, DC · On-site

Manage vendor relationships across key AI lab partners and AI vendors, tracking roadmap developments, identifying new capabilities, and exploring emerging AI tools and startups relevant to Carlyle ...

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Ai Lab information

What is an AI Lab?

An AI Lab is a specialized research and development center focused on artificial intelligence technologies. These labs typically bring together scientists, engineers, and researchers to work on advancing machine learning, data science, robotics, and related fields. AI Labs can be part of universities, tech companies, or independent organizations, and they often collaborate on cutting-edge projects, publish research, and develop AI-powered solutions for real-world problems. Their work plays a crucial role in shaping how AI is integrated into various industries and society.

What are the key skills and qualifications needed to thrive in an AI Lab, and why are they important?

To thrive in an AI Lab, you need strong expertise in machine learning, statistics, and programming, often supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and cloud computing platforms, as well as experience with data management systems, is typically required. Creative problem-solving, collaboration, and excellent communication skills help distinguish top contributors in this environment. These skills ensure effective research, innovation, and teamwork, driving successful AI development and implementation.

What are some common challenges faced when working in an AI Lab, and how can new team members overcome them?

Working in an AI Lab often involves tackling rapidly evolving technologies and collaborating with experts from diverse backgrounds, such as data scientists, engineers, and domain specialists. New team members may find it challenging to stay updated on cutting-edge research and to bridge communication gaps between different disciplines. To overcome these challenges, it's helpful to regularly attend team meetings, engage in knowledge-sharing sessions, and seek mentorship from experienced colleagues. Emphasizing continuous learning and open communication greatly enhances both individual growth and team success.

What is the difference between Ai Lab vs Data Scientist?

AspectAi LabData Scientist
Required CredentialsTypically a degree in computer science, AI, or related fields; certifications in AI/ML are commonDegree in statistics, computer science, or related fields; certifications in data analysis or machine learning are common
Work EnvironmentResearch labs, tech companies, or R&D departments focusing on AI developmentBusiness environments, analyzing data to inform decisions, often in tech, finance, or healthcare
Employer & Industry UsagePrimarily in tech companies, research institutions, and AI startupsAcross industries like finance, healthcare, marketing, and tech firms

While both roles involve working with data and algorithms, an Ai Lab focuses on developing and researching AI technologies, whereas a Data Scientist analyzes data to generate insights and support decision-making. The roles often overlap but differ mainly in their primary objectives and work environments.

How do I get into an AI lab?

To join an AI lab, candidates typically need a strong background in computer science, machine learning, or related fields, often demonstrated through a relevant degree or research experience. Gaining skills in programming languages like Python, familiarity with AI frameworks such as TensorFlow or PyTorch, and participating in research projects or internships can improve chances. Networking with professionals and publishing work can also help in securing a position in an AI lab.

What is the easiest AI Lab job to get into?

Entry-level roles in AI labs such as data annotation, data labeling, or research assistant positions are generally the easiest to obtain. These jobs often require basic technical skills, familiarity with AI concepts, and sometimes a relevant degree or certification, making them accessible for newcomers to the field.

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

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

What cities in Washington are hiring for Ai Lab jobs?

Cities in Washington with the most Ai Lab job openings:

Ai Lab jobs near you
Infographic showing various Ai Lab job openings in Washington as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Senior Data Scientist (AI)

System One

Washington, DC • Remote

Contractor

Re-posted 10 days ago

Job description

Senior Data Scientist (AI) Washington, DC – onsite presence highly preferred Period of Performance: 6 months Per Federal contract U.S. Citizenship Required Must be able to pass enhanced background screen (criminal, financial, drug) for Public Trust clearance W-2 or C2C Application Deadline: 7/27/2026 The Federal Reserve Board's Division of Consumer and Community Affairs (DCCA) is establishing an AI Lab to explore and implement generative AI and machine learning solutions that enhance staff productivity, improve analytical capabilities, and strengthen the Division's work in consumer protection and community development. We are looking for a full-stack Senior Data Scientist to support the AI Lab's research, development, and implementation of AI/ML solutions, with emphasis on generative AI applications. This role requires end-to-end ownership, from exploratory research and model development through application deployment and production maintenance. The ideal candidate is comfortable working across the full technology stack: building models, creating visualizations, developing applications, and deploying solutions to on-prem and/or cloud infrastructure. The AI Lab operates as a small, agile team where practitioners are expected to move between research, development, and deployment activities. This position will contribute to strategy while doing hands-on technical work, building models, training systems, evaluating performance, and deploying solutions. The AI Lab collaborates closely with DCCA's Data Analytics and Risk and Surveillance sections, and coordinates with the Board's enterprise technology on infrastructure, governance, and compliance matters. Required Qualifications: • U.S. citizenship • At least six years of hands-on experience developing, deploying, and maintaining AI/ML applications within a large, professional, or academic organization • Bachelor's degree in Computer Science, Data Science, Statistics, Machine Learning, or related technology field (Master's degree preferred) • Expert proficiency in Python or R for data science development; experience with additional programming languages • Production deployment experience: Demonstrated ability to build, deploy, and maintain AI/ML applications in cloud environments, including containerization and basic CI/CD practices • Application development: Proficiency building interactive applications and dashboards using frameworks such as Streamlit, Dash, Flask, RShiny, or similar • Data visualization: Strong experience creating visualizations and dashboards using Python/R libraries, Tableau, Power BI, or similar tools to communicate technical concepts to non-technical audiences • AI/ML expertise: Advanced knowledge of machine learning, NLP (text normalization, Named Entity Recognition, POS tagging, word embeddings), and Generative AI technologies; experience with frameworks such as Scikit-learn, Spacy, XGBoost • Statistical analysis: Advanced knowledge of statistical modeling, data analysis techniques, and problem-solving skills • Ability to work independently and collaboratively, taking ownership of solutions from conception through production deployment Preferred Qualifications: • Prior experience in U.S. federal government, regulatory, supervisory, or policy environments • Experience with financial services data, consumer finance, banking supervision, or regulatory data • Experience working within agile frameworks (Scrum, Kanban) and project tracking tools (Jira, Azure DevOps) • Experience with LLM APIs (GPT, Llama, Nova) and frameworks (LangChain, LlamaIndex); knowledge of prompt engineering, fine-tuning, vector databases, and semantic search • Familiarity with AWS AI services (Amazon Bedrock, SageMaker, Comprehend, Rekognition, Transcribe) • Experience building production-grade web applications with advanced user interfaces; knowledge of data storytelling and visual design principles • Experience visualizing model performance metrics, feature importance, and model explainability outputs • Hands-on experience with AWS deployment services (EC2, ECS, Lambda, S3, CloudWatch), Databricks, and infrastructure as code (Terraform, CloudFormation) • AWS certifications (Solutions Architect, Machine Learning Specialty, or similar) • Familiarity with MLOps practices including model monitoring, versioning, automated retraining, and deployment pipelines • Experience with multi-modal AI applications; understanding of responsible AI practices (bias detection, fairness evaluation, model interpretability) • Familiarity with federal IT governance frameworks (FISMA, privacy requirements) and application security in regulated environments • Experience working with sensitive or regulated data Responsibilities: AI/ML and Generative AI Development: • Research, design, and develop machine learning and artificial intelligence solutions to support DCCA's mission, with emphasis on generative AI applications • Build and iterate on proof-of-concept AI solutions that demonstrate value for specific use cases, transitioning successful prototypes into production applications • Design and implement applications leveraging large language models for text analysis, summarization, information extraction, document classification, and workflow automation • Develop prompt engineering strategies and retrieval-augmented generation (RAG) systems to improve AI application performance • Experiment with fine-tuning, model customization, and evaluation techniques to optimize AI solutions for DCCA use cases • Evaluate emerging AI technologies, frameworks, and models to identify opportunities for adoption within DCCA workflows • Apply advanced statistical and machine learning techniques including supervised/unsupervised learning, classification, regression, and deep learning methods Deployment and Operations: • Build, deploy, and maintain AI/ML models and applications in cloud environments (AWS, Kubernetes, or internal analytics platforms), working collaboratively with AI Cloud Engineers when available or independently managing end-to-end deployment • Develop interactive dashboards and analytical applications using Python frameworks (Streamlit, Dash, Flask) or R Shiny; leverage AI-assisted development tools to rapidly prototype and iterate on data products • Create data visualizations and user interfaces using Python libraries (Plotly, Matplotlib, Seaborn), R (ggplot2), Tableau, Power BI, or similar tools that translate analytical outputs into intuitive, actionable insights for non-technical audiences • Manage deployment pipelines including containerization (Docker), CI/CD practices, and GenAI application deployments with API integrations, rate limits, and cost optimization • Implement monitoring, logging, alerting, and visual dashboards for model performance, data quality, and system health; establish automated retraining pipelines and model versioning strategies • Troubleshoot and maintain deployed applications, addressing performance issues, ensuring scalability, and updating applications as requirements evolve • Support governance requirements including documentation for security assessments, privacy reviews, and compliance obligations related to deployed systems Collaboration, Communication and Agile Practices: • Work within a light agile framework, participating in sprint planning, standups, and retrospectives to coordinate work with team members • Break down technical work into manageable tasks, estimate effort, track progress, and communicate status, blockers, and technical challenges to stakeholders • Work directly with DCCA program staff economists, analysts, attorneys, and senior leadership to understand business needs, identify AI/ML opportunities, and translate requirements into technical solutions • Communicate technical concepts effectively to both technical and non-technical audiences through presentations, reports, and executive summaries • Document technical work, including code, methodologies, and project outcomes to support knowledge sharing and project continuity • Contribute to building an AI/ML practice within DCCA, including documentation, capability development, and mentoring team members Governance and Compliance Awareness: • Work within federal IT governance frameworks including FISMA, privacy, and records management requirements as they apply to AI systems • Coordinate with the Board's security, privacy, and compliance functions on matters related to AI Lab systems and applications • Apply responsible AI practices including fairness evaluation, bias detection, model interpretability, and transparency in model development • Maintain awareness of AI ethics, accountability, and appropriate use considerations in federal regulatory contexts • Support preparation of documentation for system security plans, privacy impact assessments, and authority to operate processes when required Work Environment & Schedule: • Full-time contractor position • We prefer our contractors to be onsite to collaborate with the team, but we are fully equipped to support 100% remote work arrangements • Collaborative, innovative team environment focused on exploration and rapid prototyping • Small team structure requiring versatility and initiative Ref: #851-Rockville-S1 #M1 #LI-VH1

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About System One

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System One helps employers get work done more efficiently and economically without compromising quality. Over our 35+ year history, we've helped connect thousands of talented people with innovative companies. The excitement of a perfect fit motivates us every single day.

Industry

Business consulting services and recruiting and staffing services

Company size

5,001 - 10,000 Employees

Headquarters location

Pittsburgh, PA, US

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