Cynet systems Inc
Overview
Pay Range:
$60hr - $65hr
The AI Project Manager will be responsible for planning, executing, and delivering AI solutions from ideation to production. This role involves coordinating project phases, managing risks, overseeing technical deliverables, and ensuring effective communication with stakeholders. The candidate will also contribute hands-on technical expertise, validate models, and ensure scalability while maintaining best practices in AI project governance.
Responsibilities
The AI Project Manager will be responsible for planning, executing, and delivering AI solutions from ideation to production.
This role involves coordinating project phases, managing risks, overseeing technical deliverables, and ensuring effective communication with stakeholders.
The candidate will also contribute hands-on technical expertise, validate models, and ensure scalability while maintaining best practices in AI project governance.
Project And Planning Deliverables:
Create detailed plans outlining project phases, timelines, and milestones.
Develop actionable plans for daily execution, including task assignments, resource allocation, and dependency management.
Define project scope and functional/non-functional requirements for AI solutions.
Identify potential technical and business risks with mitigation strategies.
Provide regular updates to stakeholders on project progress, key metrics, and blockers.
Technical And Operational Deliverables:
Establish and document best practices for model versioning, CI/CD pipelines.
Document technical requirements and architecture for data ingestion, processing, and feature engineering.
Create systems or reports to track and visualize KPIs for deployed models (accuracy, latency, throughput).
Define monitoring procedures for model performance and set up automated alerting for degradation.
Technical Contributions:
Develop code, model prototypes, and analytical reports.
Write scripts for data processing, feature engineering, and debugging AI issues.
Validate model functionality, identify solutions and use cases, and ensure project scalability.
Documentation And Communication Deliverables:
Provide simplified explanations of AI concepts for non-technical stakeholders.
Maintain records of key project decisions, including rationale and stakeholders involved.
Document meeting minutes to track discussions, decisions, and tasks.
Establish best practices for model explainability, fairness, and ethical considerations.
Qualifications
Experience with AI use cases, courses, or certifications.
Computer Science background, Master’s degree preferred.
Responsive, responsible, and accountable.
Proactive and quick learner.
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$60hr - $65hr
The AI Project Manager will be responsible for planning, executing, and delivering AI solutions from ideation to production. This role involves coordinating project phases, managing risks, overseeing technical deliverables, and ensuring effective communication with stakeholders. The candidate will also contribute hands-on technical expertise, validate models, and ensure scalability while maintaining best practices in AI project governance.
Responsibilities
The AI Project Manager will be responsible for planning, executing, and delivering AI solutions from ideation to production.
This role involves coordinating project phases, managing risks, overseeing technical deliverables, and ensuring effective communication with stakeholders.
The candidate will also contribute hands-on technical expertise, validate models, and ensure scalability while maintaining best practices in AI project governance.
Project And Planning Deliverables:
Create detailed plans outlining project phases, timelines, and milestones.
Develop actionable plans for daily execution, including task assignments, resource allocation, and dependency management.
Define project scope and functional/non-functional requirements for AI solutions.
Identify potential technical and business risks with mitigation strategies.
Provide regular updates to stakeholders on project progress, key metrics, and blockers.
Technical And Operational Deliverables:
Establish and document best practices for model versioning, CI/CD pipelines.
Document technical requirements and architecture for data ingestion, processing, and feature engineering.
Create systems or reports to track and visualize KPIs for deployed models (accuracy, latency, throughput).
Define monitoring procedures for model performance and set up automated alerting for degradation.
Technical Contributions:
Develop code, model prototypes, and analytical reports.
Write scripts for data processing, feature engineering, and debugging AI issues.
Validate model functionality, identify solutions and use cases, and ensure project scalability.
Documentation And Communication Deliverables:
Provide simplified explanations of AI concepts for non-technical stakeholders.
Maintain records of key project decisions, including rationale and stakeholders involved.
Document meeting minutes to track discussions, decisions, and tasks.
Establish best practices for model explainability, fairness, and ethical considerations.
Qualifications
Experience with AI use cases, courses, or certifications.
Computer Science background, Master’s degree preferred.
Responsive, responsible, and accountable.
Proactive and quick learner.
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