Senior Data & AI Engineer
Philips Bengaluru, Karnataka, India
Hospitals and Health Care · 10,001+ employees
About the role
Design, develop, and validate computer-vision models for clinical platforms while implementing robust MLOps pipelines for deployment. Collaborate with cross-functional teams to optimize model performance for both edge and cloud infrastructure while ensuring clinical safety and regulatory compliance.
What they look for
Requirements
Requires 15+ years of hands-on experience in computer vision, AI engineering, and cloud-based solution deployment. Candidates must hold a bachelor's or master's degree in a relevant technical field and possess strong expertise in deep-learning architectures and MLOps best practices.
Full description
Job Title
Senior Data & AI Engineer
Job Description
Job Title
Sr. Data & AI Engineer
Job Description
In this role, you will join a leading innovator in image-guided therapy solutions as a Senior AI Engineer for the Azurion Eye proposition, an integrated AI-enabled clinical platform. You will develop state-of-the-art AI models using live camera feed. Your work will start with proving product concepts during the Advance Development (AD) phase and productizing validated concepts into a robust, well-formed product solutions.
You will be part of the Image Guided Therapy Systems business unit with development sites in the Netherlands, China and India. This business unit is responsible for marketing, service, development and manufacturing of solutions and products used in minimally invasive procedures. You will join the global R&D department.
Key areas of responsibility
- Design, develop, train and validate computer-vision models.
- Implement multi-class object-detection and tracking solutions using CNN-based and modern deep-learning architectures (e.g. YOLO, ResNet, EfficientDet).
- Deploy machine learning models using cutting-edge technologies such as Databricks, AWS, and Kubernetes.
- Work with AWS and Bedrock for scalable AI solutions.
- Implement and manage robust MLOps pipelines for continuous integration, delivery, and monitoring of AI solutions.
- Automate model versioning, deployment, and rollback using tools like MLflow, Airflow, and ClearML.
- Collaborate with the System Engineer and Data Analytics team to define data schemas, annotation guidelines and ground-truth labelling strategies.
- Optimize models for inference performance on both edge and cloud infrastructure, ensuring real-time throughput requirements are met.
- Ensure models meet explainability, clinical safety and regulatory expectations, supporting transition from AD to PDLM production.
- Integrate advanced observability solutions (e.g., DataDog, Prometheus, Splunk, Dynatrace, Elasticsearch, Grafana) for real-time monitoring of model and system health.
- Build centralized dashboards to track AI/ML metrics, resource utilization, and user impact across environments.
- Actively participate in agile ceremonies, code reviews and technical knowledge-sharing within the team.
- Author product technical documentation, model cards and reproducible training pipeline artefacts.
To succeed in this role, you should have the following skills and experience
- 15+ years of hands-on experience developing and deploying computer-vision or imaging-AI models, AI engineering, and cloud-based solution deployment.
- Bachelor’s or master’s degree in computer science, Machine Learning, Data Science, Artificial Intelligence, or a related field.
- Computer vision – strong experience with image classification, object detection and real-time visual tracking pipelines.
- Strong expertise in MLOps best practices, model lifecycle management, and production-grade AI/ML systems.
- Imaging AI – proficiency in designing and training CNN-based architectures (YOLO, ResNet, EfficientDet, Faster R-CNN, etc.) for multi-class detection tasks.
- Python – expert-level programming for ML model development, data engineering and pipeline automation.
- Practical experience training, fine-tuning and deploying deep-learning models using PyTorch or TensorFlow
- Proficiency in leveraging AI-assisted development tools to accelerate design, coding, testing and documentation with high-quality outcomes.
- Thrives in an agile, entrepreneurial, start‑up–like environment with strong ownership, a learning mindset and the drive to rapidly iterate, validate and deliver customer-centric solutions.
- Audio signal processing – ability to complement camera-based vision models with audio-based event cues (nice to have).
Our leadership & ways of working
We look for leaders who are caring and courageous—clear storytellers who put users and patients first, and who move teams forward with conviction and humility. We expect leaders who create psychological safety, actively listen, and inspire others to bring their best selves to work. They demonstrate resilience in the face of ambiguity, take ownership during moments of complexity, and communicate with clarity and purpose.
Our leader’s role‑model collaboration across functions, markets, and geographies, fostering a culture where diverse perspectives are welcomed and valued.
Most importantly, they lead with integrity—balancing speed and rigor, championing quality and compliance, and reinforcing our shared commitment to deliver meaningful innovation that improves lives.
How we work together We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week. Onsite roles require full-time presence in the company’s facilities. Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations. About Philips Are you ready to do the work of your life to help the lives of others? Learn more about our business, discover our rich and exciting history and learn more about our purpose. If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our culture of impact with care.
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