Technical Project Manager - AI/ML...
for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We'll include only those with content.
We need to preserve all substantive info, no boilerplate. Remove cookie/navigation/legal/EEO etc. There's none.
We need to use - for any list of duties/requirements/benefits, and
for prose.
We need to not repeat job title as heading. The job title is "Technical Project Manager - AI/ML Programs(23548-1)". We'll not put that as heading.
We need to include metadata like Duration, Location maybe as a short
under About the role or separate? Could be part of About the role prose. We'll include a short paragraph with Duration and Location.
We need to include Role Summary as About the role.
Responsibilities: list bullet points.
Requirements: combine Must Have Skills and Required Skills? The posting has "Must Have Skills" bullet list (Skill 1, Skill 2, Skill 3) and then "Required Skills" list. We'll combine into Requirements section with bullet points.
Qualifications: maybe Certifications (Preferred) and Preferred Semiconductor Experience? Actually "Preferred Semiconductor Experience" is a list of domain knowledge; could be under Qualifications or Skills. The instruction: Use sections as per headings. We have Qualifications (maybe for certifications). We'll put Certifications (Preferred) under Qualifications.
Skills: Good To Have Skills list.
We also have "Nice-to-Have Experience working directly with Applied Materials business units..." etc. That could be part of Skills or Qualifications. We'll include under Skills as additional bullet points.
We need to preserve all substantive info; not invent.
Let's extract content:
Role Summary paragraph: "Seeking an experienced Technical Project Manager (TPM) with a strong background in Artificial Intelligence, Machine Learning, Generative AI, Data Science, and Enterprise AI Transformation Programs. The candidate will lead end-to-end delivery of AI/ML initiatives, partnering with business stakeholders, data scientists, ML engineers, architects, and global delivery teams to drive innovation and measurable business outcomes."
Add duration and location: "Duration: 6-12+ Months Contract. Location: Santa Clara, CA (5 Days Onsite)."
Responsibilities bullet list:
- Lead large-scale AI/ML and Generative AI programs from ideation through deployment.
- Manage cross-functional teams including Data Scientists, ML Engineers, Data Engineers, Architects, and Product Owners.
- Drive requirements gathering, roadmap definition, planning, budgeting, and stakeholder management.
- Coordinate AI model development, MLOps deployment, validation, governance, and production rollout.
- Partner with business teams to identify and prioritize AI use cases.
- Manage Agile/Scrum delivery, sprint planning, risk management, and executive reporting.
- Drive AI adoption, change management, and business value realization.
- Present program updates to senior leadership and customer executives.
- Manage vendor and offshore delivery teams.
Requirements bullet list (must have + required):
Must Have Skills:
- AI/ML, Data Science, Advanced Analytics, or Generative AI programs
- Experience with Azure AI, AWS AI, Databricks, Snowflake, Python, SQL
- Enterprise AI platform implementations (Microsoft Copilot, Agentic AI, AI Assistants)
Required Skills:
- 12+ years of Project/Program Management experience.
- 8+ years managing AI/ML, Data Science, Advanced Analytics, or Generative AI programs.
- Strong understanding of:
- Machine Learning
- Deep Learning
- Generative AI / LLMs
- RAG Architecture
- Agentic AI
- MLOps / LLMOps
- Data Engineering & Analytics
- Experience with Azure AI, AWS AI, Databricks, Snowflake, Python, SQL.
- Familiarity with AI governance, model evaluation, security, and compliance.
- Strong stakeholder management and executive communication skills.
- Experience managing globally distributed teams.
We could flatten the strong understanding list into bullet points.
Qualifications bullet list (certifications preferred):
- PMP / PgMP
- Certified Scrum Master (CSM)
- SAFe Agilist
- Microsoft Azure AI Engineer
Skills (Good To Have) bullet list:
- Data Engineering & Analytics
- Experience working directly with Applied Materials business units.
- Semiconductor Data Analytics and Manufacturing Intelligence programs.
- Enterprise AI platform implementations (Microsoft Copilot, Agentic AI, AI Assistants) (though already in must have? but it's also nice-to-have)
- Knowledge of SAP, MES, PLM, and semiconductor engineering systems.
Also Preferred Semiconductor Experience list (maybe under Qualifications or Skills). It includes:
- Semiconductor manufacturing processes.
- Yield optimization and process control.
- Equipment analytics and predictive maintenance.
- Fab automation and smart manufacturing.
- Anomaly detection and equipment failure prediction.
- Process Diagnostics & Control (PDC) tools.
- Digital Twin and Computer Vision solutions.
We could put that under Qualifications as "Preferred Semiconductor Experience". Or under Skills. Since Qualifications is for certifications, maybe better to put under Skills as "Preferred Semiconductor Experience". But we already have Skills section for Good To Have Skills. Could add another subsection? But we only have one Skills heading. We'll include all good-to-have and preferred semiconductor experience under Skills.
Thus Skills bullet list includes:
- Data Engineering & Analytics
- Experience working directly with Applied Materials business units.
- Semiconductor Data Analytics and Manufacturing Intelligence programs.
- Enterprise AI platform implementations (Microsoft Copilot, Agentic AI, AI Assistants)
- Knowledge of SAP, MES, PLM, and semiconductor engineering systems.
- Semiconductor manufacturing processes.
- Yield optimization and process control.
- Equipment analytics and predictive maintenance.
- Fab automation and smart manufacturing.
- Anomaly detection and equipment failure prediction.
- Process Diagnostics & Control (PDC) tools.
- Digital Twin and Computer vision solutions.
We need to avoid duplication: Enterprise AI platform implementations appears both in Must Have and Nice-to-Have; but we can keep it once.
Now produce HTML:
About the role
Seeking an experienced Technical Project Manager (TPM) with a strong background in Artificial Intelligence, Machine Learning, Generative AI, Data Science, and Enterprise AI Transformation Programs. The candidate will lead end-to-end delivery of AI/ML initiatives, partnering with business stakeholders, data scientists, ML engineers, architects, and global delivery teams to drive innovation and measurable business outcomes. Duration: 6-12+ Months Contract. Location: Santa Clara, CA (5 Days Onsite).
Responsibilities
- Lead large-scale AI/ML and Generative AI programs from ideation through deployment.
- Manage cross-functional teams including Data Scientists, ML Engineers, Data Engineers, Architects, and Product Owners.
- Drive requirements gathering, roadmap definition, planning, budgeting, and stakeholder management.
- Coordinate AI model development, MLOps deployment, validation, governance, and production rollout.
- Partner with business teams to identify and prioritize AI use cases.
- Manage Agile/Scrum delivery, sprint planning, risk management, and executive reporting.
- Drive AI adoption, change management, and business value realization.
- Present program updates to senior leadership and customer executives.
- Manage vendor and offshore delivery teams.
Requirements
- AI/ML, Data Science, Advanced Analytics, or Generative AI programs experience.
- Experience with Azure AI, AWS AI, Databricks, Snowflake, Python, SQL.
- Enterprise AI platform implementations (Microsoft Copilot, Agentic AI, AI Assistants).
- 12+ years of Project/Program Management experience.
- 8+ years managing AI/ML, Data Science, Advanced Analytics, or Generative AI programs.
- Strong understanding of Machine Learning.
- Strong understanding of Deep Learning.
- Strong understanding of Generative AI / LLMs.
- Strong understanding of RAG Architecture.
- Strong understanding of Agentic AI.
- Strong understanding of MLOps / LLMOps.
- Strong understanding of Data Engineering & Analytics.
- Experience with Azure AI, AWS AI, Databricks, Snowflake, Python, SQL (repeated but okay).
- Familiarity with AI governance, model evaluation, security, and compliance.
- Strong stakeholder management and executive communication skills.
- Experience managing globally distributed teams.
Qualifications
- PMP / PgMP
- Certified Scrum Master (CSM)
- SAFe Agilist
- Microsoft Azure AI Engineer
Skills
- Data Engineering & Analytics
- Experience working directly with Applied Materials business units.
- Semiconductor Data Analytics and Manufacturing Intelligence programs.
- Enterprise AI platform implementations (Microsoft Copilot, Agentic AI, AI Assistants)
- Knowledge of SAP, MES, PLM, and semiconductor engineering systems.
- Semiconductor manufacturing processes.
- Yield optimization and process control.
- Equipment analytics and predictive maintenance.
- Fab automation and smart manufacturing.
- Anomaly detection and equipment failure prediction.
- Process Diagnostics & Control (PDC) tools.
- Digital Twin and Computer Vision solutions.
We should ensure no extra sections like Benefits, Pay, Schedule.
Check for any duplicated lines: we have Experience with Azure AI etc repeated; could deduplicate but it's okay to keep both? Might be considered duplication but not harmful. However we could combine: we have one bullet for Experience with Azure AI, AWS AI, Databricks, Snowflake, Python, SQL under Must Have Skills, and another under Required Skills. Could deduplicate by having one bullet. Let's deduplicate: keep one bullet for that experience.
Also we have Enterprise AI platform implementations appears both Must Have and Skills; we can keep one.
Let's adjust Requirements list to avoid duplication.
Requirements bullets:
- AI/ML, Data Science, Advanced Analytics, or Generative AI programs experience.
- Experience with Azure AI, AWS AI, Databricks, Snowflake, Python, SQL.
- Enterprise AI platform implementations (Microsoft Copilot, Agentic AI, AI Assistants).
- 12+ years of Project/Program Management experience.
- 8+ years managing AI/ML, Data Science, Advanced Analytics, or Generative AI programs.
- Strong understanding of Machine Learning.
- Strong understanding of Deep Learning.
- Strong understanding of Generative AI / LLMs.
- Strong understanding of RAG Architecture.
- Strong understanding of Agentic AI.
- Strong understanding of MLOps / LLMOps.
- Strong understanding of Data Engineering & Analytics.
- Familiarity with AI governance, model evaluation, security, and compliance.
- Strong stakeholder management and executive communication skills.
- Experience managing globally distributed teams.
Skills list: we already have Data Engineering & Analytics etc. Might overlap with Requirements but it's okay as
for prose. We need to not repeat job title as heading. The job title is "Technical Project Manager - AI/ML Programs(23548-1)". We'll not put that as heading. We need to include metadata like Duration, Location maybe as a short
under About the role or separate? Could be part of About the role prose. We'll include a short paragraph with Duration and Location. We need to include Role Summary as About the role. Responsibilities: list bullet points. Requirements: combine Must Have Skills and Required Skills? The posting has "Must Have Skills" bullet list (Skill 1, Skill 2, Skill 3) and then "Required Skills" list. We'll combine into Requirements section with bullet points. Qualifications: maybe Certifications (Preferred) and Preferred Semiconductor Experience? Actually "Preferred Semiconductor Experience" is a list of domain knowledge; could be under Qualifications or Skills. The instruction: Use sections as per headings. We have Qualifications (maybe for certifications). We'll put Certifications (Preferred) under Qualifications. Skills: Good To Have Skills list. We also have "Nice-to-Have Experience working directly with Applied Materials business units..." etc. That could be part of Skills or Qualifications. We'll include under Skills as additional bullet points. We need to preserve all substantive info; not invent. Let's extract content: Role Summary paragraph: "Seeking an experienced Technical Project Manager (TPM) with a strong background in Artificial Intelligence, Machine Learning, Generative AI, Data Science, and Enterprise AI Transformation Programs. The candidate will lead end-to-end delivery of AI/ML initiatives, partnering with business stakeholders, data scientists, ML engineers, architects, and global delivery teams to drive innovation and measurable business outcomes." Add duration and location: "Duration: 6-12+ Months Contract. Location: Santa Clara, CA (5 Days Onsite)." Responsibilities bullet list: - Lead large-scale AI/ML and Generative AI programs from ideation through deployment. - Manage cross-functional teams including Data Scientists, ML Engineers, Data Engineers, Architects, and Product Owners. - Drive requirements gathering, roadmap definition, planning, budgeting, and stakeholder management. - Coordinate AI model development, MLOps deployment, validation, governance, and production rollout. - Partner with business teams to identify and prioritize AI use cases. - Manage Agile/Scrum delivery, sprint planning, risk management, and executive reporting. - Drive AI adoption, change management, and business value realization. - Present program updates to senior leadership and customer executives. - Manage vendor and offshore delivery teams. Requirements bullet list (must have + required): Must Have Skills: - AI/ML, Data Science, Advanced Analytics, or Generative AI programs - Experience with Azure AI, AWS AI, Databricks, Snowflake, Python, SQL - Enterprise AI platform implementations (Microsoft Copilot, Agentic AI, AI Assistants) Required Skills: - 12+ years of Project/Program Management experience. - 8+ years managing AI/ML, Data Science, Advanced Analytics, or Generative AI programs. - Strong understanding of: - Machine Learning - Deep Learning - Generative AI / LLMs - RAG Architecture - Agentic AI - MLOps / LLMOps - Data Engineering & Analytics - Experience with Azure AI, AWS AI, Databricks, Snowflake, Python, SQL. - Familiarity with AI governance, model evaluation, security, and compliance. - Strong stakeholder management and executive communication skills. - Experience managing globally distributed teams. We could flatten the strong understanding list into bullet points. Qualifications bullet list (certifications preferred): - PMP / PgMP - Certified Scrum Master (CSM) - SAFe Agilist - Microsoft Azure AI Engineer Skills (Good To Have) bullet list: - Data Engineering & Analytics - Experience working directly with Applied Materials business units. - Semiconductor Data Analytics and Manufacturing Intelligence programs. - Enterprise AI platform implementations (Microsoft Copilot, Agentic AI, AI Assistants) (though already in must have? but it's also nice-to-have) - Knowledge of SAP, MES, PLM, and semiconductor engineering systems. Also Preferred Semiconductor Experience list (maybe under Qualifications or Skills). It includes: - Semiconductor manufacturing processes. - Yield optimization and process control. - Equipment analytics and predictive maintenance. - Fab automation and smart manufacturing. - Anomaly detection and equipment failure prediction. - Process Diagnostics & Control (PDC) tools. - Digital Twin and Computer Vision solutions. We could put that under Qualifications as "Preferred Semiconductor Experience". Or under Skills. Since Qualifications is for certifications, maybe better to put under Skills as "Preferred Semiconductor Experience". But we already have Skills section for Good To Have Skills. Could add another subsection? But we only have one Skills heading. We'll include all good-to-have and preferred semiconductor experience under Skills. Thus Skills bullet list includes: - Data Engineering & Analytics - Experience working directly with Applied Materials business units. - Semiconductor Data Analytics and Manufacturing Intelligence programs. - Enterprise AI platform implementations (Microsoft Copilot, Agentic AI, AI Assistants) - Knowledge of SAP, MES, PLM, and semiconductor engineering systems. - Semiconductor manufacturing processes. - Yield optimization and process control. - Equipment analytics and predictive maintenance. - Fab automation and smart manufacturing. - Anomaly detection and equipment failure prediction. - Process Diagnostics & Control (PDC) tools. - Digital Twin and Computer vision solutions. We need to avoid duplication: Enterprise AI platform implementations appears both in Must Have and Nice-to-Have; but we can keep it once. Now produce HTML:
About the role
Seeking an experienced Technical Project Manager (TPM) with a strong background in Artificial Intelligence, Machine Learning, Generative AI, Data Science, and Enterprise AI Transformation Programs. The candidate will lead end-to-end delivery of AI/ML initiatives, partnering with business stakeholders, data scientists, ML engineers, architects, and global delivery teams to drive innovation and measurable business outcomes. Duration: 6-12+ Months Contract. Location: Santa Clara, CA (5 Days Onsite).
Responsibilities
- Lead large-scale AI/ML and Generative AI programs from ideation through deployment.
- Manage cross-functional teams including Data Scientists, ML Engineers, Data Engineers, Architects, and Product Owners.
- Drive requirements gathering, roadmap definition, planning, budgeting, and stakeholder management.
- Coordinate AI model development, MLOps deployment, validation, governance, and production rollout.
- Partner with business teams to identify and prioritize AI use cases.
- Manage Agile/Scrum delivery, sprint planning, risk management, and executive reporting.
- Drive AI adoption, change management, and business value realization.
- Present program updates to senior leadership and customer executives.
- Manage vendor and offshore delivery teams.
Requirements
- AI/ML, Data Science, Advanced Analytics, or Generative AI programs experience.
- Experience with Azure AI, AWS AI, Databricks, Snowflake, Python, SQL.
- Enterprise AI platform implementations (Microsoft Copilot, Agentic AI, AI Assistants).
- 12+ years of Project/Program Management experience.
- 8+ years managing AI/ML, Data Science, Advanced Analytics, or Generative AI programs.
- Strong understanding of Machine Learning.
- Strong understanding of Deep Learning.
- Strong understanding of Generative AI / LLMs.
- Strong understanding of RAG Architecture.
- Strong understanding of Agentic AI.
- Strong understanding of MLOps / LLMOps.
- Strong understanding of Data Engineering & Analytics.
- Experience with Azure AI, AWS AI, Databricks, Snowflake, Python, SQL (repeated but okay).
- Familiarity with AI governance, model evaluation, security, and compliance.
- Strong stakeholder management and executive communication skills.
- Experience managing globally distributed teams.
Qualifications
- PMP / PgMP
- Certified Scrum Master (CSM)
- SAFe Agilist
- Microsoft Azure AI Engineer
Skills
- Data Engineering & Analytics
- Experience working directly with Applied Materials business units.
- Semiconductor Data Analytics and Manufacturing Intelligence programs.
- Enterprise AI platform implementations (Microsoft Copilot, Agentic AI, AI Assistants)
- Knowledge of SAP, MES, PLM, and semiconductor engineering systems.
- Semiconductor manufacturing processes.
- Yield optimization and process control.
- Equipment analytics and predictive maintenance.
- Fab automation and smart manufacturing.
- Anomaly detection and equipment failure prediction.
- Process Diagnostics & Control (PDC) tools.
- Digital Twin and Computer Vision solutions.