Intern Computer Vision Deep Learning Engineer Jobs in Virginia

Job Summary

Client is seeking a highly skilled AI/ML Full Stack Developer to design, develop, and deploy modern fullstack applications enhanced with advanced Artificial Intelligence capabilities. This role blends frontend and backend engineering with Generative AI, RAG pipelines, ML model development, MLOps, and enterprisescale cloud deployment. You will collaborate with architects, software engineers, data engineers, and business stakeholders to translate requirements into productiongrade AI-powered software solutions. The ideal candidate brings strong software engineering fundamentals combined with handson experience developing and operationalizing AI/ML systems on Microsoft Azure.

Major Responsibilities

Full Stack Application Development

Develop and maintain modern web applications using React, React Native, HTML, CSS, JavaScript/TypeScript

Build backend services and REST/GraphQL APIs using Node.js and microservices-based patterns

Design, optimize, and execute complex SQL queries across multiple relational and nonrelational database systems

Implement secure, scalable integrations with cloud, data, and AI services.

Participate in code reviews, architecture discussions, and Agile ceremonies.

Utilize Git/GitHub for version control and DevOps workflows

Apply software design patterns and best practices in full-stack development.

Generative AI & Retrieval-Augmented Generation (LLM Applications)

Build LLM powered applications for text generation, summarization, Q&A, conversational AI, and enterprise knowledge search.

Develop RAG pipelines using embeddings, vector databases, knowledge bases, and grounding techniques with enterprise data.

Implement Azure OpenAI, Cognitive Search, and related services to build secure, compliant GenAI solutions.

Integrate LLMs into backend applications, microservices, and enterprise platforms.

Optimize prompts, system instructions, and orchestration patterns to ensure quality, reliability, and cost efficiency.

AI Agents & Agentic Automation

Design and implement single agent and multi agent systems for intelligent automation and decisioning.

Build autonomous and semi-autonomous agents that perceive, plan, act, and interact with tools, APIs, and event-driven systems.

Develop agentic workflows for complex enterprise processes using Azure and modern orchestration frameworks.

ML Model Based AI (Classical ML & Deep Learning)

Design, develop, and deploy classical ML and deep learning models using platforms such as Azure Machine Learning, PyTorch, and Scikit Learn.

Perform data preprocessing, feature engineering, model training, hyperparameter tuning, validation, and performance optimization.

Ensure resilience, scalability, and lifecycle management for all production models.

Work with large-scale datasets, performing data preprocessing, feature engineering, and model validation.

Deploy AI models using cloud-based platforms such as Azure AI/ML,.

Ensure AI/ML solutions align with enterprise security, compliance, and governance standards.

Education and Experience Requirements:

Requires bachelor's degree (or international equivalent) and 7 + years of relevant experience or 11+ years of relevant work experience without degree

3-5 years of experience in AI/ML development, including designing and deploying ML models.

3-5 years in Full Stack Development Experience

Knowledge, understanding and practical experience of web & mobile development technologies such as HTML, CSS, React & React Native, JavaScript/TypeScript.

Good understanding of latest front-end frameworks and backend technologies

Practical knowledge and work experience with NodeJS, Reactjs, React-Native and GraphQL.

Good knowledge and understanding of RESTful API principles.

Good understanding of relational databases and querying using SQL.

Strong software engineering background (Python, REST APIs, microservices, event-driven systems).

Hands-on experience with Azure Machine Learning, Azure OpenAI, Cognitive Services, and Azure Data Lake.

Experience building RAG systems, vector embeddings, and knowledge retrieval pipelines.

Proficiency in big data processing technologies such as Databricks, Azure Data Factory, or Kafka.

Experience with multi-agent systems or agentic AI orchestration frameworks.

Background in NLP, computer vision, or advanced deep learning architectures.

Experience with vector databases (Azure AI Search vector store).

Expertise in AI/ML frameworks like PyTorch, Keras, or Scikit-learn.

Experience with NLP, Computer Vision, Deep Learning, and Generative AI models.

Strong knowledge of MLOps, CI/CD for AI model deployment, and containerization (Docker, Kubernetes).

Familiarity with data engineering, ETL pipelines, and SQL/NoSQL databases.

Experience working in an enterprise environment with large-scale AI deployments.

Strong analytical, problem-solving, and communication skills.

Preferred Skills:

Experience with the Microsoft Agent Framework, Azure AI Foundry and Agent Service, Microsoft 365 Agents SDK/Toolkit, Semantic Kernel (including AutoGen convergence), RAG and vector based retrieval pipelines for agents, and enterprise grade agent tooling and integrations. based retrieval pipelines for agents, and enterprise grade agent tooling and integrations.

Experience in Multiagent orchestration patterns, Advanced retrieval for agents: GraphRAG, structured data tools (NL2SQL), and domain specific agents. agent orchestration patterns specific agents