AI/ML Engineer - MLOps & Enterprise Data

AI/ML Engineer – MLOps & Enterprise Data Atlanta, GA (Mostly remote with occasional onsite meetings) W2 Contract Only About the Role We are seeking an AI/ML Engineer to help our client build and operationalize enterprise AI/ML capabilities across their organization.

This role will sit at the intersection of machine learning engineering, MLOps, data engineering, and knowledge management.

The ideal candidate has hands-on experience taking machine learning models from development through testing, evaluation, deployment, and ongoing production monitoring.

They will also contribute to the development of an enterprise data and knowledge layer that brings together data from across the organization and makes it accessible for AI, analytics, and business use cases.

This is an opportunity to work on foundational AI capabilities, including enterprise data aggregation, knowledge graphs, ML pipelines, model evaluation, production ML, and MLOps.

Key Responsibilities Design, develop, test, deploy, and maintain machine learning models and AI/ML solutions in production.Develop and implement processes for model evaluation, validation, testing, and performance measurement.Establish approaches for testing and validating ML models both before deployment and while models are running in production.Develop and maintain MLOps pipelines and processes supporting the full machine learning lifecycle.Monitor models in production for performance, accuracy, reliability, drift, and other key metrics.Build automated processes for model deployment, monitoring, retraining, and versioning.Contribute to an enterprise data and knowledge layer that can be leveraged by teams across the organization.Aggregate and integrate data from multiple enterprise sources to support AI/ML and analytics use cases.Help design and build knowledge graphs, semantic data structures, and other approaches for connecting and organizing enterprise knowledge.Develop data and ML pipelines that make enterprise information accessible to downstream AI applications and users.Partner with data engineers, software engineers, data scientists, architects, and business stakeholders.Help establish engineering standards and best practices around production ML, MLOps, model testing, and AI system reliability.Evaluate emerging AI/ML technologies and determine how they can be incorporated into the organization's enterprise AI capabilities.

Required Qualifications 3+ years of experience in machine learning engineering, AI/ML engineering, or a closely related field.Strong Python development skills.Hands-on experience developing and deploying machine learning models into production.Strong understanding of machine learning concepts, model evaluation, validation, and testing.Experience with the full ML lifecycle, from model development through deployment and production monitoring.Hands-on MLOps experience.Experience monitoring and troubleshooting machine learning models in production, including understanding of model performance degradation and drift.Experience building or working with data pipelines and enterprise data platforms.Experience integrating and aggregating data from multiple sources.Experience with knowledge graphs, graph databases, ontologies, semantic layers, or similar knowledge representation technologies.Strong understanding of software engineering practices, version control, testing, and CI/CD.Experience working in cloud-based environments such as AWS, Azure, or GCP.Bachelor's Degree required.

Preferred Qualifications Experience with MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML, or similar MLOps platforms.Experience with Docker and Kubernetes.Experience with Spark/PySpark or other large-scale data processing technologies.Experience with Neo4j, Amazon Neptune, RDF/SPARQL, or other graph technologies.Experience with RAG, GraphRAG, vector databases, semantic search, or LLM-based applications.Experience building enterprise AI/ML platforms or shared services used by multiple teams.Experience with automated model testing, model monitoring, and ML CI/CD.Experience working with large-scale or complex enterprise data environments.

What We're Looking For The ideal candidate is more than a traditional Data Scientist. We're looking for an engineer who can take ML models and AI capabilities beyond experimentation and into reliable, scalable production environments.

About GSquared Group: Shouldn’t your recruiting partner put as much effort and value into your career as you do? With GSquared Group, we take the time to understand where you would like to take your career and what is important to you.

GSquared Group is a woman-owned boutique technology services company in the Atlanta area. Founded in 2010, we are a premier provider of IT talent search, management consulting, and software development services.

We support a diverse client base that spans all industries and includes Fortune 100 to mid-market companies. We offer direct hire placement, contract, and contract-to-hire positions.

We are proud to be known by our community for putting relationships at the core of everything we do.

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 opportunitiesA family-friendly environmentNice bonuses for referralsA culture that supports you and your career Hear what others are saying on Glassdoor: https://www.glassdoor.com/Reviews/GSquared-Group-Reviews-E651488.htm?filter.iso3Language=eng