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Ai Applications Engineer Jobs in Virginia (NOW HIRING)

Node.Digital

Senior AI/ML Engineer

Herndon, VA · On-site

$107K - $147K/yr

Senior AI/ML Engineer Location: Herndon, VA (Hybrid Work) Preferred: US Citizenship Node.Digital is ... You will focus on building generative AI applications with embedded artifcial intelligence or ...

Node.Digital

Senior AI/ML Engineer

Herndon, VA · On-site

$107K - $147K/yr

Senior AI/ML Engineer Location: Herndon, VA (Hybrid Work) Preferred: US Citizenship Node.Digital is ... You will focus on building generative AI applications with embedded artifcial intelligence or ...

ECS

AI Test Engineer

Ashburn, VA · On-site

Everforth ECS is seeking an AI Testing Engineer to work minimum of 3 business days onsite at our ... The development and execution of test plans for AI models and applications, identifying ...

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Ai Applications Engineer information

What is an AI applications engineer?

AI Applications Engineers are professionals who design, develop, and integrate artificial intelligence (AI) solutions into software applications to solve real-world problems. They work closely with data scientists, software engineers, and business stakeholders to build and deploy machine learning models, automate processes, and enhance user experiences. Their responsibilities often include selecting appropriate AI technologies, writing code, testing models, and optimizing performance. AI Applications Engineers play a key role in translating AI research and prototypes into scalable and maintainable products used in industries like healthcare, finance, retail, and more.

What are the key skills and qualifications needed to thrive as an AI applications engineer?

To thrive as an AI Applications Engineer, you need strong programming abilities (Python, Java, or C++), a solid understanding of machine learning algorithms, and a relevant degree in computer science or engineering. Familiarity with AI frameworks (such as TensorFlow or PyTorch), cloud platforms, and data processing tools is typically required, along with certifications in machine learning or AI. Excellent problem-solving, collaboration, and communication skills help you translate business needs into effective AI solutions and work efficiently with cross-functional teams. These skills are critical for building scalable, reliable AI systems that deliver tangible value to organizations.

How does an AI applications engineer typically collaborate with data scientists and software developers on project teams?

As an AI Applications Engineer, you will often serve as a bridge between data scientists, who build and optimize machine learning models, and software developers, who integrate these models into production systems. Collaboration usually involves translating model requirements into scalable application features, ensuring model outputs align with user needs, and troubleshooting technical challenges that arise during deployment. Regular meetings, code reviews, and shared documentation are common practices to keep everyone aligned and ensure seamless integration. This cross-functional teamwork enhances both the technical robustness and usability of AI-powered applications.

What is the difference between Ai Applications Engineer vs Data Scientist?

AspectAi Applications EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; knowledge of AI/ML toolsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops AI solutions, collaborates with engineering teamsAnalyzes data, builds models, interprets results
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, tech, research institutions

While both roles involve AI and data, Ai Applications Engineers focus on developing and deploying AI solutions in engineering contexts, whereas Data Scientists analyze data to extract insights. The roles often overlap but differ mainly in their primary focus and application environment.

What does an AI applications engineer do?

An AI applications engineer designs, develops, and implements artificial intelligence solutions to solve specific business problems. They work with machine learning models, data processing, and programming tools like Python or TensorFlow, often collaborating with data scientists and software developers to deploy AI systems effectively.

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Cities in Virginia with the most Ai Applications Engineer job openings:

Ai Applications Engineer jobs near you

Senior AI/ML Engineer

Node.Digital

Herndon, VA • On-site

$107K - $147K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 25 days ago

Job description

Senior AI/ML Engineer

Location: Herndon, VA (Hybrid Work)

Preferred: US Citizenship

Node.Digital is an innovative solutions development company that combines agile development services with next-generation technologies in Cloud, Mobile, and AI/Machine Learning. We deliver state-of-the-art enterprise solutions to both government and commercial clients. We are looking for talented people to join our efforts to enable digitalization of organizations with AI Automation and Machine Learning.

Role: AI/ML Engineer

The AI/ML Engineer is the architect and guardian of intelligent automation solutions that incorporate generative AI and machine learning technologies. They ensure the operational efciency and continuous refnement of integrated AI/ML solutions with a strong focus on modern generative AI engineering.

Requirements

Required Skills:

  • Overall experience of 6-10 Years working on Application/framework development
  • Min 5+ years of exp in AI/ML-based app/solution development with strong focus on generative AI applications
  • Hands-on experience with AWS services including Amazon Bedrock, S3, SageMaker, CDK,Lambda, and other AI/ML services
  • Experience with generative AI models and frameworks (LLMs, RAG architectures, prompt engineering, model fne-tuning)
  • Hands-on exp with OCR, ICR and OMR technologies is a must
  • Good programming knowledge in Python and relevant ML/AI frameworks (TensorFlow, PyTorch, LangChain)
  • Good understanding of Document Processing, classifcation, data extraction is a must
  • Knowledge in Natural Language Processing (NLP), Deep Learning, and Generative AI is a must
  • Hands-on Web application/APIs Development experience is a must
  • Profciency in asynchronous/multi-threaded programming
  • Strong knowledge of algorithms, data structures, complexity, optimization, caching and security
  • Experience with JSON, SOAP, Rest, XML, XHTML, XSD and XSLT
  • Strong knowledge of object-oriented concepts and Database concepts Experience with databases like SQL Server, PostgreSQL
  • Experience with NoSQL databases and vector databases (for RAG implementations) is a plus
  • Knowledge of AWS cloud architecture patterns and serverless computing
  • Experience with CI/CD pipelines and DevSecOps practices
  • Knowledge of Agile methodologies is desirable
  • Experience working with a toolchain that includes TFS, SVN, Git
  • Involved in different phases of SDLC and have good working exposure on different SDLCs like Agile Methodologies

Responsibility:

Your responsibility spans the design, maintenance, and optimization of intelligent automation solutions including AI Center troubleshooting and resolution of issues that might arise post-implementation. You will focus on building generative AI applications with embedded artifcial intelligence or machine learning in support of continuous improvement, learning and augmented decision-making.

Key responsibilities include:

Designing and implementing generative AI solutions using Amazon Bedrock, foundation models, and RAG architectures

Building repeatable intelligent solutions/bots for document processing and data cleansing

Developing and deploying scalable ML/AI models on AWS infrastructure

Creating API endpoints and integrations for AI/ML services

Implementing model evaluation, monitoring, and continuous improvement processes Collaborating with cross-functional teams to embed AI capabilities across business functions

Nice to Have:

Experience with front-end frameworks (React, Angular, Vue.js) and modern web development UiPath RPA Developer Certifcation and UiPath AI Center Experience

Knowledge of chatbot development and conversational AI

Experience with AWS Bedrock Agents and Guardrails

Familiarity with model distillation and prompt optimization techniques

Understanding of responsible AI practices and AI security

Recommended Certifcations:

AWS Certifed Machine Learning – Specialty

AWS Certifed Solutions Architect

General AI/ML Certifcations (TensorFlow Developer, Azure AI Engineer

UiPath AI Center Experience (nice to have)

Eucation/Year of Exp:

Bachelor's degree and a minimum of 5 years of experience in automation engineering roles with a focus on AI/ML integrations and generative AI application development

Cultural Fit:

Effective communication skills for technical discussions

Comfortable with Agile methodologies

Ability to work remotely

Alignment with customer's mission and values

Adaptability to varying organizational structures

Data Analysis and Data Architecture Skills

Strong problem-solving abilities for complex AI/ML challenges

Benefits

  • Medical
  • Dental
  • Vision
  • Basic Life
  • Health Saving Account
  • 401K Matching
  • Three weeks of PTO/Sick
  • 11 Paid Holidays
  • Pre-Approved Online Training