Archived listing. The details below describe a past opening.
Required Skills & Experience
Bachelor’s degree with equivalent experience in Computer Science, Data Science, Engineering, Statistics, Machine Learning or a related discipline. 4+ years of experience developing machine-learning or advanced analytics solutions. Strong Python skills. Experience with common ML/data-science frameworks and libraries. Experience taking analytical or ML solutions from experimentation into production. Strong foundation in statistics, experimentation, model evaluation and data analysis. Experience working with cloud-based data and compute environments. Experience with APIs, software-development practices, source control and CI/CD. Demonstrated ability to translate business or operational problems into analytical approaches.
Job Description
Insight Global is seeking an Applied AI/ML Engineer- Data Scientist to develop and operationalize the intelligence layer of off-prem platform. This role will combine data science, machine learning, generative AI and software engineering to create intelligent capabilities that help users understand operational information, diagnose issues, identify anomalies, retrieve knowledge, and make better decisions. Unlike a traditional research-focused Data Scientist position, this role emphasizes taking AI capabilities from experimentation through production deployment and evaluation. Design, develop, evaluate and deploy AI/ML capabilities Develop analytical models for anomaly detection, asset health, forecasting, classification and other operational use cases. Develop generative AI and agentic capabilities using enterprise-approved foundation models and AI platforms. Design prompts, tools, agents, workflows and orchestration patterns. Develop Retrieval-Augmented Generation (RAG) and knowledge-retrieval solutions when appropriate. Create rigorous evaluation frameworks for LLM and agent behavior. Establish metrics for model accuracy, relevance, reliability, hallucination, latency and cost. Develop guardrails and validation mechanisms for AI-generated responses. Collaborate with Data Engineering to define training, inference, retrieval and feature-data requirements. Collaborate with the Full Stack/Cloud Engineer to deploy AI services into production. Develop prototypes rapidly while designing solutions that can transition into production. Monitor model and agent performance and continuously improve deployed capabilities. Communicate model behavior and analytical findings to engineers, product stakeholders and operational subject-matter experts. Stay current with emerging AI, agentic AI, ML and data-science technologies and assess their applicability.
$65-$75