Junior AI​/ML Engineer

Location: Primarily remote but must be local to the Atlanta area for occasional onsite meetings.

Employment Type: Contract-to-Hire (W2 Only)

We are seeking a highly skilled and hands‑on AI/ML Engineer to help design, build, and deploy enterprise‑grade AI solutions that deliver measurable business value. This is not a research‑focused role—we are looking for an engineer who has successfully taken AI solutions from concept to production and has experience developing scalable, production‑ready AI applications.

The ideal candidate has experience building and deploying AI‑powered applications, agentic systems, and retrieval architectures, including leveraging knowledge graphs to improve contextual understanding and reasoning capabilities within AI systems. This individual will partner closely with engineering, product, and business teams to develop intelligent solutions that can be adopted across the organization.

• Design, develop, and deploy production‑ready AI and machine learning solutions that address complex business problems.
• Build and implement AI applications utilizing Large Language Models (LLMs), Generative AI, and agentic frameworks.
• Design and develop knowledge graphs to model relationships between data entities and enhance contextual reasoning capabilities.
• Build Retrieval‑Augmented Generation (RAG) architectures leveraging vector databases and knowledge graph technologies.
• Develop scalable data pipelines for data ingestion, transformation, embedding generation, and model inference.
• Evaluate, fine‑tune, and optimize AI models for performance, accuracy, scalability, and cost efficiency.
• Implement guardrails, observability, monitoring, and governance practices for enterprise AI solutions.
• Collaborate with software engineers, data engineers, architects, and business stakeholders to integrate AI capabilities into enterprise applications and workflows.
• Establish best practices for AI engineering, model deployment, testing, and operational support.
• Stay current with emerging AI technologies, frameworks, and methodologies and identify opportunities for adoption.

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field. Equivalent practical experience will also be considered.
• 3+ years of software engineering experience with at least 1+ years building and deploying AI/ML solutions in production environments.
• Demonstrated experience delivering production‑ready AI applications from proof of concept through deployment and operational support.
• Hands‑on experience with Large Language Models (LLMs), Generative AI, and AI agent development.
• Experience building and implementing Retrieval‑Augmented Generation (RAG) solutions.
• Hands‑on experience designing and implementing knowledge graphs and graph‑based data models.
• Experience with graph databases such as Neo4j, Amazon Neptune, or similar technologies.
• Strong programming experience in Python and familiarity with software engineering best practices.
• Experience with APIs, microservices, and cloud‑native application development.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Strong understanding of machine learning concepts, embeddings, vector search, and model evaluation techniques.
• Experience implementing AI governance, monitoring, and observability practices in production environments.

• Experience with AI orchestration frameworks such as Lang Chain, Lang Graph, Llama Index, or similar technologies.
• Experience with vector databases such as Pinecone, Weaviate, Chroma, or Azure AI Search.
• Experience deploying models using containerization and orchestration technologies such as Docker and Kubernetes.
• Experience building enterprise AI assistants, copilots, or multi‑agent systems.
• Experience implementing semantic search, entity extraction, and graph‑based reasoning capabilities.
• Experience working within highly collaborative, cross‑functional Agile environments.

• Deliver production‑grade AI solutions that are scalable, secure, and maintainable.
• Build intelligent applications capable of contextual reasoning through knowledge graphs and retrieval architectures.
• Accelerate the organization's adoption of AI by delivering solutions that solve real business problems and provide measurable outcomes.
• Serve as a technical leader and trusted partner in establishing enterprise AI engineering best practices.

• Competitive & Comprehensive Healthcare Package (available only for W2 hourly consultants)
• Simple IRA with company match (available only for W2 hourly consultants)
• Professional development & networking opportunities
• A family‑friendly environment
• Nice bonuses for referrals
• A culture that supports you and your career