Technical Project Manager

Dawar Consulting, Inc.; Ann Arbor (MI); On-site; USD 124,000 - 143,000; Full time

Job summary

Dawar Consulting, Inc. in Ann Arbor, MI, seeks a Technical Project Manager with a strong background in ENOVIA PLM, AI/ML initiatives, and technical project delivery to lead enterprise projects.

You will coordinate data scientists, PLM developers, cloud engineers, and business stakeholders to scope, plan, and deploy AI-enabled PLM solutions, ensuring governance, data privacy, and risk mitigation throughout the lifecycle.

Qualifications

• 7+ years of ENOVIA PLM development, implementation, or solution delivery.
• 2+ years delivering AI/ML or data science projects.
• 2+ years of project/program management delivering AI/ML/data science solutions.
• Strong understanding of the Machine Learning Lifecycle (data preparation, model development, training, evaluation, deployment).
• Experience coordinating software engineers, data engineers, data scientists, and PLM developers.
• Experience with JIRA, Confluence, and Git.
• Experience with at least one cloud platform: AWS, Azure, or GCP.

Responsibilities

• Lead PLM AI/ML initiatives from scoping to delivery, managing timelines, deliverables, risks, and issues.
• Coordinate cross-functional teams to ensure successful solution delivery.
• Oversee end-to-end AI/ML lifecycle within ENOVIA PLM workflows.
• Drive governance, data privacy, compliance, and risk mitigation.

Skills

ENOVIA PLM

AI/ML initiatives

Cross-functional collaboration

Stakeholder management

Project planning

Risk management

Tools

JIRA

Confluence

Git

AWS/Azure/GCP

ENOVIA PLM

Job description

Technical Project Manager

Ann Arbor, United States

Our client, a world leader in the semiconductor industry, is looking for a Technical Project Manager - Enovia PLM based at Ann Arbor, MI

Job Duration: Long Term Contract (Possibility Of Extension)

Pay Rate: $90/hr on W2

We are seeking an experienced Technical Project Manager with a strong background in ENOVIA PLM solutions, AI/ML initiatives, and technical project delivery.

This individual will work closely with data scientists, software engineers, PLM teams, business stakeholders, and vendors to deliver AI/ML solutions within the ENOVIA PLM environment.

• Lead PLM AI/ML initiatives from project scoping and planning through execution, deployment, launch, and delivery, while managing timelines, deliverables, dependencies, risks, and technical issues.
• Coordinate cross-functional teams including data scientists, engineers, ENOVIA PLM developers, cloud teams, business stakeholders, and external vendors to ensure successful solution delivery.
• Oversee the end-to-end AI/ML lifecycle, including data preparation, model development, training, evaluation, validation, deployment, performance monitoring, and integration within ENOVIA PLM workflows.
• Drive stakeholder communication, AI governance, data privacy, compliance, and risk mitigation, addressing data quality, model performance, infrastructure, scalability, and implementation challenges.

Required Qualifications

• 7+ years of experience in ENOVIA PLM development, implementation, or solution delivery.
• 2+ years of experience supporting or delivering AI/ML or data science projects and solutions.
• 2+ years of project or program management experience, specifically delivering technical solutions involving AI, Machine Learning, or Data Science.
• Strong understanding of the Machine Learning Lifecycle, including data preparation, model development, training, evaluation, and deployment.
• Experience coordinating technical teams, including software engineers, data engineers, data scientists, and PLM developers.
• Experience with JIRA, Confluence, and Git.
• Experience working with at least one cloud platform: AWS, Azure, or GCP.
• Strong skills in project planning, risk management, stakeholder management, and cross-functional collaboration.

Preferred Skills

• Experience integrating AI/ML solutions into PLM applications and enterprise environments.
• Experience with cloud-based AI/ML deployment and data pipelines.
• Knowledge of Responsible AI, AI governance, data privacy, fairness, and model transparency.
• Familiarity with Agile, Scrum, or other technical project delivery methodologies.