Process Optimization Project Manager

Vrinda Global; Kastūrināyanipalli; On-site; INR 2,800,000 - 4,800,000; Full time

Job summary

Vrinda Global seeks an experienced Project Manager to lead AI-enabled, digital-led process optimization initiatives in battery and component manufacturing. You will drive design, development, and execution of optimization strategies to improve throughput, quality, and SPC adherence across processes.

The role requires collaborating with Operations, Engineering, IT, and OT teams to enable advanced control on the shop floor and translate results into SOPs and sustained improvements.

Qualifications

• 7–12 years in Process Engineering, CI, and AI applications in manufacturing.
• Experience with AI-enabled process optimization across metal forming, casting, and finishing.
• Strong understanding of DoE, regression, and time-series analytics.

Responsibilities

• Lead digital-led process engineering and SOP updates.
• Quantify upstream/downstream impact on yield, quality and cost.
• Coordinate with IT, OT, and Operations teams for automation on the shop floor.
• Manage vendor/OEM relationships for critical machines and sensors.
• Guide instrumentation and PLC teams on feedback loops and setpoints.
• Drive quality improvement and material utilization through closed-loop control.

Skills

AI & Process Modeling

Regression analysis

Time-series analytics

DoE (Design of Experiments)

Six Sigma mindset

Stakeholder management

Education

B.E./B.Tech in Chemical Engineering

B.E./B.Tech in Mechanical Engineering

B.E./B.Tech in Instrumentation Engineering

Equivalent discipline

Tools

Ignition

Power BI

Rockwell HMI

Python

Minitab/JMP

SQL

Job description

Job Description Process Optimization Project Manager

Role: Process Optimization PM

Job Summary

Organization is looking for an experienced Project Manager to lead the organization's digital-led process optimization initiatives as part of the Manufacturing Operations Center of Excellence.

The role will drive the design, development, and execution of AI-enabled process optimization and recommendation strategies aligned with business objectives to improve throughput, quality, and tighter Statistical Process Control (SPC) across battery and component manufacturing processes.

The ideal candidate will collaborate effectively with site and enterprise Operations, Engineering (Process and Product), IT, and OT teams to enable digital and automation systems for advanced and closed-loop process control on the shop floor.

Key Responsibilities

1. Digital-Led Process Engineering

• Drive AI/ML and Design of Experiments (DoE)-based optimization of parameters across:
• Plate preparation
• Casting
• Pasting
• Curing
• Formation in battery manufacturing
• Injection molding in components
• Use Six Sigma, regression, and simulation tools to fine-tune process setpoints and process changes.

2. End-to-End Impact Thinking

• Quantify the impact of upstream setpoints on downstream yield, quality, and cost.
• Build cross-process visibility, including processes such as casting and COS finishing.

3. Change Management

• Facilitate engagement between operators, supervisors, and engineers/PCT teams.
• Translate optimization results into SOP updates.
• Coordinate with Process and Operations teams for SOP implementation.

4. Vendor Management

• Partner with IT, Engineering, and OT teams to establish business requirements and align dependencies.
• Manage OEM relationships for critical machines.
• Ensure best-in-class controls and sensing systems are in place.

5. Sensor/Actuator Expertise

• Guide instrumentation and PLC teams to improve:
• Feedback loops
• Digital setpoint control
• Sensor alignment

6. Value Orientation

• Drive quality improvement and material-consumption optimization through real-time setpoint optimization and closed-loop actuation systems on critical machines and processes.

Required Skills

AI & Process Modeling

• Understanding of regression, clustering, DoE, and time-series analytics.
• In-depth knowledge of metal casting, thermal curing, and molding processes.
• Knowledge of feedback loops such as PID and multilinear systems.

Tools & Systems

• Experience with:
• Ignition
• Power BI
• Rockwell HMI systems
• Python, Minitab/JMP, and SQL preferred.

Soft Skills

• Ability to align Process Engineers and plant leadership to drive process changes.
• Strong stakeholder management skills.
• Comfortable working with shop-floor teams.
• Local language proficiency in Telugu/Tamil preferred.

Good to Have

Industry 4.0 Technologies

• Understanding of Industry 4.0 principles and their applications, including:
• Smart manufacturing
• Connected systems

Digital Tooling Awareness

• Knowledge of AI, Data Science, and IoT systems.
• Experience with digital product development.

Qualifications & Experience

Work Experience

• 7–12 years of experience in:
• Process Engineering
• Continuous Improvement (CI)
• AI applications in manufacturing

Educational Qualification

• B.E./B.Tech in:
• Chemical Engineering
• Mechanical Engineering
• Instrumentation Engineering
• Equivalent discipline

Preferred Certifications

• Six Sigma Black Belt / Green Belt.
• AI for Industry certification would be an added advantage.