Mid-Level AI/ML Engineer

GSquared Group; Atlanta (GA); On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

Competitive & Comprehensive Healthcare Package

Simple IRA with company match

Professional development opportunities

Family-friendly environment

Bonuses for referrals

Supportive culture

Job summary

GSquared Group is seeking an AI/ML Engineer to design, build, and deploy enterprise-grade AI solutions. The ideal candidate will have a strong background in producing scalable AI applications and be local to Atlanta for occasional onsite meetings.

This role focuses on developing AI and machine learning solutions that solve complex business problems, requiring hands-on experience with AI frameworks, cloud platforms, and data modeling.

Benefits include competitive healthcare and professional development opportunities.

Qualifications

• 3+ years of software engineering experience with 1+ years in AI/ML solutions.
• Proven experience delivering production-ready AI applications.
• Strong programming experience in Python.

Responsibilities

• Design and deploy production-ready AI and ML solutions.
• Build AI applications utilizing Large Language Models and Generative AI.
• Develop scalable data pipelines for data processing and model inference.

Skills

Python

Large Language Models (LLMs)

Generative AI

AI governance and observability

Knowledge graphs

Cloud platforms (AWS, Azure, GCP)

Education

Bachelor's degree in Computer Science, Engineering, or Data Science

Tools

Neo4j

Docker

Kubernetes

Job description

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

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

Position Overview

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.

Responsibilities

• 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.

Required Qualifications

• 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.

Preferred Qualifications

• Experience with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, 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.

What Success Looks Like

• 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.

GSquared Benefits

• 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