Project Manager AI ML

Gyansys Infotech; Bengaluru; Hybrid; INR 1,800,000 - 3,000,000; Full time

Job summary

Gyansys Infotech in Bengaluru, India is seeking a Project Manager – AI/ML to lead end-to-end delivery of AI/ML and GenAI initiatives across enterprise environments. This role collaborates with AI/ML engineers, data teams, platform, security, and business stakeholders to ensure projects have clear scope, predictable timelines, strong governance, and production readiness.

The ideal candidate has 6–10 years of experience managing AI/ML, GenAI, or data-driven projects in an enterprise setting, with

Qualifications

• In-depth understanding of ML/DL and hyperscalar AI solutions (Azure preferred).
• Led GenAI and ML/DL deployments; SDLC, ROI calculation, and business use-case presentation.

Responsibilities

• Lead AI/ML project delivery from intake and planning through execution, rollout, and closure.
• Define scope, success criteria, and support effort/cost estimation (VROM).
• Establish and manage project governance using Jira boards and Confluence spaces.
• Coordinate cross-functional teams across AI/ML, Data, Engineering, Platform, Security, and Operations.
• Track progress, risks, dependencies, and mitigation plans; communicate status to stakeholders and leadership.
• Ensure infra, data access, security, and compliance readiness for AI/ML solutions across DEV/QA/PROD.
• Support rollout, transition, documentation, and operational handoff.
• Capture lessons learned and contribute to DIA delivery practices.

Skills

AI/ML PM

Stakeholder mgmt

Agile delivery

Jira & Confluence use

Tools

Jira

Confluence

Azure

Job description

Project Manager AI/ML

Location: Bengaluru, India (Hybrid : Work from Office)

Experience : 6-10 Yrs

Role Overview

We are seeking a Project Manager – AI/ML to lead the end to end delivery of AI/ML and GenAI initiatives across Applied Materials. This role partners closely with AI/ML engineers, data teams, platform, security, and business stakeholders to ensure projects are delivered with clear scope, predictable timelines, strong governance, and production readiness.

Key Responsibilities

• Must Have : Indepth understanding of ML, DL, Hyperscalar AI Solutions (Preferred Azure)
• Must Have: Worked on multiple GenAI and ML/DL Solution deployment. Expertise in entire SDLC, project closure, ROI calculation, Business use case presentation etc.
• Lead AI/ML project delivery from intake and planning through execution, rollout, and closure
• Drive requirements kickoff, define scope and success criteria, and support effort and cost estimation (VROM)
• Establish and manage project governance, including Jira boards, Confluence spaces, milestones, and delivery cadence
• Coordinate cross functional teams across AIML, Data, Engineering, Platform, Security, and Operations
• Track progress, risks, dependencies, and mitigation plans; communicate status to stakeholders and leadership
• Ensure infra, data access, security, and compliance readiness for AI/ML solutions across DEV/QA/PROD
• Support rollout, transition, documentation, and operational handoff
• Capture lessons learned and contribute to continuous improvement of DIA delivery practices

Skills & Experience

• Experience managing AI/ML, GenAI, or data driven projects in an enterprise environment
• Strong understanding of Agile and hybrid delivery models
• Excellent stakeholder management and cross team coordination skills
• Hands on experience with Jira, Confluence, and modern delivery tooling
• Ability to manage ambiguity, dependencies, and technical trade offs effectively
• Good to have: Knowledge of the semiconductor domain and experience working on semiconductor or manufacturing focused products
• Good to have: Prior product management experience, including exposure to roadmaps, product requirements, or business driven prioritization

Preferred Qualifications

• PMP or similar project management certification (preferred)
• Experience working with cloud platforms, data pipelines, or AI/ML platforms
• Exposure to governance, security, or compliance processes in enterprise environments

What Success Looks Like

• AI/ML initiatives delivered on time, within scope, and with high quality
• Stakeholders aligned and informed throughout the project lifecycle
• Solutions deployed with strong governance, scalability, and operational readiness