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Resource Logistics Inc.
Posted 74 days agoVerified live 2d ago
AI Engineer
Brief overview
Remote
2+ yrsMinimum
PythonMachine learning frameworksTensorFlowPyTorchAI agents developmentMachine learning model deploymentMicrosoft ClientureDatabricksFabricMicrosoft AI FoundryGenAI modelsLarge language modelsPlanning algorithmsDecision-making frameworksReinforcement learning
About the company
R
Resource Logistics Inc.resource-logistics.com
Resource Logistics is an information technology company providing ERP, CRM implementation, software solutions, and staffing services.
Job description
Summary
Resource Logistics Inc. is a company focused on AI solutions, and they are seeking an AI Engineer to develop and deploy intelligent AI agents and machine learning models. The role involves collaborating across teams to optimize AI performance and contribute to innovative projects.
Responsibilities
- Demonstrate deep expertise in cloud technologies, with a strong focus on Microsoft Clienture, including expertise in Clienture Data and AI platforms (such as Databricks, Fabric, and AI Foundry)
- Build and experiment with GenAI models and agentic workflows
- Design and implement intelligent AI agents leveraging large language models (LLMs), planning algorithms, and decision-making frameworks
- Build secure, scalable AI agents and integrate into applications and workflows for robust, cross-platform deployment and enhanced user experience
- Advance AI agent capabilities through reseClienth and performance evaluation, focusing on improved conversation, decision-making, adaptability, and the implementation of safety and guardrail mechanisms
- Continuously optimize agent performance through feedback mechanisms, reinforcement learning, and user interaction analysis
- Collaborate across the stack, supporting backend services, model pipelines, and frontend interfaces for agentic systems
- Prototype rapidly, iterate on ideas, and contribute to incubation efforts in a startup-style environment
- Work closely with senior engineers and reseClienthers, learning best practices and contributing to production-grade AI systems
Skills
- Proficient in Python and other relevant programming languages
- 3 years of hands-on experience with machine learning frameworks and libraries (such as TensorFlow, PyTorch, or similar)
- 2 years of hands-on experience in developing and deploying AI agents and machine learning models
- Demonstrate deep expertise in cloud technologies, with a strong focus on Microsoft Clienture, including expertise in Clienture Data and AI platforms (such as Databricks, Fabric, and AI Foundry)
- Build and experiment with GenAI models and agentic workflows
- Design and implement intelligent AI agents leveraging large language models (LLMs), planning algorithms, and decision-making frameworks
- Build secure, scalable AI agents and integrate into applications and workflows for robust, cross-platform deployment and enhanced user experience
- Advance AI agent capabilities through research and performance evaluation, focusing on improved conversation, decision-making, adaptability, and the implementation of safety and guardrail mechanisms
- Continuously optimize agent performance through feedback mechanisms, reinforcement learning, and user interaction analysis
- Collaborate across the stack, supporting backend services, model pipelines, and frontend interfaces for agentic systems
- Prototype rapidly, iterate on ideas, and contribute to incubation efforts in a startup-style environment
- Work closely with senior engineers and researchers, learning best practices and contributing to production-grade AI systems
Qualifications
Must Haves
- Proficient in Python and other relevant programming languages
- 3 years of hands-on experience with machine learning frameworks and libraries (such as TensorFlow, PyTorch, or similar)
- 2 years of hands-on experience in developing and deploying AI agents and machine learning models
- Demonstrate deep expertise in cloud technologies, with a strong focus on Microsoft Clienture, including expertise in Clienture Data and AI platforms (such as Databricks, Fabric, and AI Foundry)
- Build and experiment with GenAI models and agentic workflows
- Design and implement intelligent AI agents leveraging large language models (LLMs), planning algorithms, and decision-making frameworks
- Build secure, scalable AI agents and integrate into applications and workflows for robust, cross-platform deployment and enhanced user experience
- Advance AI agent capabilities through research and performance evaluation, focusing on improved conversation, decision-making, adaptability, and the implementation of safety and guardrail mechanisms
- Continuously optimize agent performance through feedback mechanisms, reinforcement learning, and user interaction analysis
- Collaborate across the stack, supporting backend services, model pipelines, and frontend interfaces for agentic systems
- Prototype rapidly, iterate on ideas, and contribute to incubation efforts in a startup-style environment
- Work closely with senior engineers and researchers, learning best practices and contributing to production-grade AI systems
