Note: The job is a remote job and is open to candidates in USA. GSquared Group is a woman-owned boutique technology services company providing IT talent search, management consulting, and software development services. The AI/ML Engineer will build and operationalize enterprise AI/ML capabilities, develop MLOps pipelines, deploy and monitor production models, and contribute to enterprise data layers and knowledge graphs.
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
Skills
- • 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
- • 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
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
- Mostly remote with occasional onsite meetings
Company Overview