AI/ML Engineer

Insight Global
Newark, NJ, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Cloud Computing Cloud Database Continuous Integration Data Governance Distributed Systems Graph Database Python (Programming Language) Machine Learning NoSQL Tensorflow Software Deployment
+15 more
Software Engineering SQL Databases Data Ingestion Pytorch Large Language Models Multi-Agent Systems Deep Learning AI Platforms Scikit Learn Virtual Agents Restful APIs Software Version Control Data Pipelines Devsecops Microservices

Job description

Insight Global is hiring an experienced AI/ML Engineer to support one of its largest financial services clients. This individual will independently engineer and deploy machine learning and agentic AI solutions while partnering with Data Scientists, Data Engineers, Data Analysts, DevSecOps, and other cross-functional teams to build scalable, production-ready systems. The role will focus on architecting semantic knowledge layers, knowledge graphs, and Graph RAG capabilities that enable AI agents and LLMs to reason over complex business data. Day to day, you will develop data ingestion, retrieval, semantic, and memory pipelines, build and optimize AI applications using Python and SQL, and leverage cloud technologies to deliver enterprise-scale solutions. Additionally, you will support ontology management, data governance, CI/CD automation, testing, monitoring, and deployment best practices while collaborating with stakeholders to solve complex business and technical challenges.

Requirements

  • 3-5 years of experience developing and deploying machine learning, deep learning, and Agentic AI solutions in production environments
  • Experience with LLMs, multi-agent systems, and Graph RAG
  • Strong software engineering background, including system design, microservices, REST APIs, distributed systems, CI/CD, testing, and version control
  • Hands-on experience with Python and SQL, along with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn
  • Experience building scalable data ingestion, transformation, retrieval, and processing pipelines
  • Strong understanding of model deployment, monitoring, validation, explainability, drift detection, and AI governance
  • Experience with relational, NoSQL, and graph databases, as well as cloud-based data and AI platforms

Knowledge of statistics, probability, machine learning algorithms, and predictive modeling techniques Experience with knowledge graphs, semantic retrieval, and ontology-driven architectures.

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