Description:

Role Overview

We are seeking an AI Manager to build and scale our Artificial Intelligence Center of Excellence, with an immediate focus on Image Processing and Vision Inspection systems used in pharma manufacturing environments, with hands-on expertise in OpenCV, C++, Image Segmentation, Machine Learning, and AI-driven vision algorithms.

This role requires a hands-on, execution-driven AI leader with deep expertise in computer vision, real-time image processing, and AI-based inspection, combined with the ability to build production-grade AI systems under real-world constraints such as latency, accuracy, robustness, and hardware limitations.

The role will lead a team of AI engineers, own end-to-end AI delivery, and progressively expand the CoEs scope beyond vision inspection into broader AI capabilities, including multimodal AI, predictive intelligence, and modern applied AI advancements.

Key Responsibilities :

1. Technical Leadership Vision, Applied AI & Production Systems

- Provide technical leadership for computer vision and applied AI, owning architecture, execution quality, and production outcomes.

- Architect, design, and optimize real-time vision inspection solutions for detection, segmentation, classification, measurement, OCR, and anomaly detection.

Lead development of modern AI models, including :

- CNNs, Vision Transformers, hybrid and multi-head architectures

- U-Net, YOLO variants, OCR pipelines

- Generative models for synthetic data generation and augmentation

Build hybrid pipelines combining classical image processing and deep learning to address :

- Class imbalance and rare defects

- Lighting variation, noise, motion blur, and environmental drift

- Own the end-to-end AI lifecycle :

- Data acquisition, annotation strategy, augmentation, and dataset governance

- Model training, validation, benchmarking, and deployment

- Continuous monitoring, drift detection, retraining, and optimization

- Drive edge AI and performance optimization, balancing accuracy, latency, and compute cost through :

- Quantization, pruning, distillation, and compression

- Hardware-accelerated inference (TensorRT, ONNX, OpenVINO, CUDA)

Establish production-grade MLOps pipelines, including :

- Dataset and model versioning

- CI/CD for models and inference services

- Automated testing, deployment, rollback, and observability

- Expand AI CoE capabilities beyond inspection into:

Predictive and prescriptive analytics :

- Applied AI for operational and manufacturing intelligence

- Gen AI capabilities

2. Optical Systems, Imaging Hardware & Industrial Integration

- Provide technical leadership for industrial imaging system design and integration, including:

- Cameras (Area scan, Line scan, CMOS/CCD, global/rolling shutter)

- Interfaces (GigE Vision, USB3 Vision, CoaXPress, CameraLink)

- Optics (telecentric, macro, low-distortion lenses; C/F mount)

- Lighting systems (dome, ring, coaxial, backlight, strobe, IR, structured)

- Define end-to-end imaging architectures, considering:

- FOV, DOF, resolution, magnification

- Distortion, dynamic range, and signal-to-noise ratio (SNR)

- Lead calibration and validation methodologies, including:

- Intrinsic and extrinsic calibration

- Geometric transforms and homography

- Color and illumination normalization

- Build and validate robust optical setups for high-speed inspection, minimizing motion blur, vibration, and environmental variability.

- Work cross-functionally with mechanical, electrical, automation, and platform teams to ensure reliable system-level performance under:

- Ensure compliance with industrial and regulatory standards (GMP, cGMP, pharma, FMCG, CPG, medical devices, automotive, packaging).

- Support FAT, SAT, and field deployments, including root-cause analysis and performance tuning.

Team Leadership & Delivery Excellence:

- Build, mentor, and scale a high-performing AI/ML engineering team with strong applied and production-first mindset.

- Establish technical standards and best practices for:

- Drive execution using agile delivery practices, including sprint planning, task breakdown, and delivery tracking.

- Lead code reviews, design reviews, and technical signoffs to ensure quality and scalability.

- Collaborate closely with Product, QA, and Operations teams to deliver field-ready, reliable AI systems.

- Act as the technical and execution face of the AI CoE, translating business problems into scalable AI roadmaps and measurable outcomes.

Required Technical Skills :

Core AI & Computer Vision :

- Advanced proficiency in C++ (C++11/14/17) and OpenCV for high-performance vision pipelines.

- Strong experience in image segmentation and inspection, using classical and deep learning approaches.

- Hands-on experience with ML/DL models :

- Strong foundation in real-time processing :

- Multi-threading, parallelization, performance optimization

- Solid mathematical grounding in:

- Linear algebra, geometry, optimization, probability, signal processing

- Edge AI, MLOps & Software Engineering

- Experience with model optimization and edge deployment:

- Experience with REST/gRPC APIs for system integration.

Preferred Experience:

- Worked in pharmaceutical, packaging, automotive, or manufacturing industries.

- Experience with :

- Prior experience developing production-grade image-processing software used by end customers

5. Behavioural & Leadership Competencies

- Strong problem-solving mindset with ability to break down complex imaging challenges.

- Excellent communication and documentation skills.

- Ability to manage multiple projects and prioritise under aggressive timelines.

- Takes full ownership of technology decisions and outcomes.

- Mentors and elevates team skill levels through guidance and code reviews.

What This Role Enables:

- Opportunity to build a world-class Vision & AI Centre of Excellence

- Ownership of algorithmic strategy for next-gen high-performance inspection systems

- Work with cutting-edge imaging hardware, optics, and industrial automation